{"authorized": false, "total": 149, "sortKeys": [{"key": "publicationdate-desc", "label": "Publication date (Newest First)"}, {"key": "publicationdate-asc", "label": "Publication date (Oldest First)"}, {"key": "downloads-desc", "label": "Downloads (High to Low)"}, {"key": "downloads-asc", "label": "Downloads (Low to High)"}, {"key": "title-asc", "label": "Title (Ascending)"}, {"key": "title-desc", "label": "Title (Descending)"}, {"key": "id-asc", "label": "Pipeline ID (Ascending)"}, {"key": "id-desc", "label": "Pipeline ID (Descending)"}], "filterKeys": [{"key": "tags", "values": ["aqua", "bids", "bigbrain", "bioinformatics", "blast", "boutiques", "brainstorm", "connectome", "diffusion", "diffusion mri", "dmri", "dwi", "eeg", "eegnet", "fmri", "fnirs", "fuzzy", "genetic", "glm", "image processing", "mri", "multiple-sclerosis", "neuroimaging", "neuroimaing", "neuroinformatics", "nifti", "noise", "norms", "nuclear medicine", "quality", "segmentation", "testing"]}], "elements": [{"id": "zenodo.1482743", "title": "fsl_bet", "description": "Automated brain extraction tool for FSL", "publicationdate": "2018-11-10", "deprecated": false, "downloads": 92047, "author": "Oxford Centre for Functional MRI of the Brain (FMRIB)", "version": "1.0.0", "doi": "10.5281/zenodo.1482743", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "mri"]}, "toolversion": "1.0.0", "name": "fsl_bet", "descriptorurl": "https://github.com/aces/cbrain-plugins-neuro/blob/master/cbrain_task_descriptors/fsl_bet.json", "commandline": "bet [INPUT_FILE] [MASK] [FRACTIONAL_INTENSITY] [VERTICAL_GRADIENT] [CENTER_OF_GRAVITY] [OVERLAY_FLAG] [BINARY_MASK_FLAG] [APPROX_SKULL_FLAG] [NO_SEG_OUTPUT_FLAG] [VTK_VIEW_FLAG] [HEAD_RADIUS] [THRESHOLDING_FLAG] [ROBUST_ITERS_FLAG] [RES_OPTIC_CLEANUP_FLAG] [REDUCE_BIAS_FLAG] [SLICE_PADDING_FLAG] [MASK_WHOLE_SET_FLAG] [ADD_SURFACES_FLAG] [ADD_SURFACES_T2] [VERBOSE_FLAG] [DEBUG_FLAG]", "containerimage": {"image": "mcin/docker-fsl:latest", "index": "index.docker.io", "type": "docker"}, "inputs": [{"description": "Input image (e.g. img.nii.gz)", "value-key": "[INPUT_FILE]", "type": "File", "optional": false, "id": "infile", "name": "Input file"}, {"description": "Output brain mask (e.g. img_bet.nii.gz)", "value-key": "[MASK]", "type": "String", "optional": false, "id": "maskfile", "name": "Mask file"}, {"command-line-flag": "-f", "description": "Fractional intensity threshold (0->1); default=0.5; smaller values give larger brain outline estimates", "value-key": "[FRACTIONAL_INTENSITY]", "type": "Number", "maximum": 1, "minimum": 0, "integer": false, "optional": true, "id": "fractional_intensity", "name": "Fractional intensity threshold"}, {"command-line-flag": "-g", "description": "Vertical gradient in fractional intensity threshold (-1->1); default=0; positive values give larger brain outline at bottom, smaller at top", "value-key": "[VERTICAL_GRADIENT]", "type": "Number", "maximum": 1, "minimum": -1, "integer": false, "optional": true, "id": "vg_fractional_intensity", "name": "Vertical gradient fractional intensity threshold"}, {"command-line-flag": "-c", "description": "The xyz coordinates of the center of gravity (voxels, not mm) of initial mesh surface. Must have exactly three numerical entries in the list (3-vector).", "value-key": "[CENTER_OF_GRAVITY]", "type": "Number", "list": true, "max-list-entries": 3, "optional": true, "id": "center_of_gravity", "min-list-entries": 3, "name": "Center of gravity vector"}, {"command-line-flag": "-o", "description": "Generate brain surface outline overlaid onto original image", "value-key": "[OVERLAY_FLAG]", "type": "Flag", "optional": true, "id": "overlay_flag", "name": "Overlay flag"}, {"command-line-flag": "-m", "description": "Generate binary brain mask", "value-key": "[BINARY_MASK_FLAG]", "type": "Flag", "optional": true, "id": "binary_mask_flag", "name": "Binary mask flag"}, {"command-line-flag": "-s", "description": "Generate rough skull image (not as clean as betsurf)", "value-key": "[APPROX_SKULL_FLAG]", "type": "Flag", "optional": true, "id": "approx_skull_flag", "name": "Approximate skull flag"}, {"command-line-flag": "-n", "description": "Don't generate segmented brain image output", "value-key": "[NO_SEG_OUTPUT_FLAG]", "type": "Flag", "optional": true, "id": "no_seg_output_flag", "name": "No segmented brain image flag"}, {"command-line-flag": "-e", "description": "Generate brain surface as mesh in .vtk format", "value-key": "[VTK_VIEW_FLAG]", "type": "Flag", "optional": true, "id": "vtk_mesh", "name": "VTK format brain surface mesh flag"}, {"command-line-flag": "-r", "description": "head radius (mm not voxels); initial surface sphere is set to half of this", "value-key": "[HEAD_RADIUS]", "type": "Number", "optional": true, "id": "head_radius", "name": "Head Radius"}, {"command-line-flag": "-t", "description": "Apply thresholding to segmented brain image and mask", "value-key": "[THRESHOLDING_FLAG]", "type": "Flag", "optional": true, "id": "thresholding_flag", "name": "Threshold segmented image flag"}, {"command-line-flag": "-R", "description": "More robust brain center estimation, by iterating BET with a changing center-of-gravity.", "value-key": "[ROBUST_ITERS_FLAG]", "type": "Flag", "optional": true, "id": "robust_iters_flag", "name": "Robust iterations flag"}, {"command-line-flag": "-S", "description": "This attempts to cleanup residual eye and optic nerve voxels which bet2 can sometimes leave behind. This can be useful when running SIENA or SIENAX, for example. Various stages involving standard-space masking, morphpological operations and thresholdings are combined to produce a result which can often give better results than just running bet2.", "value-key": "[RES_OPTIC_CLEANUP_FLAG]", "type": "Flag", "optional": true, "id": "residual_optic_cleanup_flag", "name": "Residual optic cleanup flag"}, {"command-line-flag": "-B", "description": "This attempts to reduce image bias, and residual neck voxels. This can be useful when running SIENA or SIENAX, for example. Various stages involving FAST segmentation-based bias field removal and standard-space masking are combined to produce a result which can often give better results than just running bet2.", "value-key": "[REDUCE_BIAS_FLAG]", "type": "Flag", "optional": true, "id": "reduce_bias_flag", "name": "Bias reduction flag"}, {"command-line-flag": "-Z", "description": "This can improve the brain extraction if only a few slices are present in the data (i.e., a small field of view in the Z direction). This is achieved by padding the end slices in both directions, copying the end slices several times, running bet2 and then removing the added slices.", "value-key": "[SLICE_PADDING_FLAG]", "type": "Flag", "optional": true, "id": "slice_padding_flag", "name": "Slice padding flag"}, {"command-line-flag": "-F", "description": "This option uses bet2 to determine a brain mask on the basis of the first volume in a 4D data set, and applies this to the whole data set. This is principally intended for use on FMRI data, for example to remove eyeballs. Because it is normally important (in this application) that masking be liberal (ie that there be little risk of cutting out valid brain voxels) the -f threshold is reduced to 0.3, and also the brain mask is \"dilated\" slightly before being used.", "value-key": "[MASK_WHOLE_SET_FLAG]", "type": "Flag", "optional": true, "id": "whole_set_mask_flag", "name": "Mask-whole-set flag"}, {"command-line-flag": "-A", "description": "This runs both bet2 and betsurf programs in order to get the additional skull and scalp surfaces created by betsurf. This involves registering to standard space in order to allow betsurf to find the standard space masks it needs.", "value-key": "[ADD_SURFACES_FLAG]", "type": "Flag", "optional": true, "id": "additional_surfaces_flag", "name": "Additional surfaces flag"}, {"command-line-flag": "-A2", "description": "This is the same as -A except that a T2 image is also input, to further improve the estimated skull and scalp surfaces. As well as carrying out the standard space registration this also registers the T2 to the T1 input image.", "value-key": "[ADD_SURFACES_T2]", "type": "File", "optional": true, "id": "additional_surfaces_t2", "name": "Additional surfaces with T2"}, {"command-line-flag": "-v", "description": "Switch on diagnostic messages", "value-key": "[VERBOSE_FLAG]", "type": "Flag", "optional": true, "id": "verbose_flag", "name": "Verbose Flag"}, {"command-line-flag": "-d", "description": "Don't delete temporary intermediate images", "value-key": "[DEBUG_FLAG]", "type": "Flag", "optional": true, "id": "debug_flag", "name": "Debug Flag"}], "groups": [{"description": "Specify parameters that alter the default BET functionality", "id": "optional_params_group", "members": ["fractional_intensity", "vg_fractional_intensity", "center_of_gravity", "overlay_flag", "binary_mask_flag", "approx_skull_flag", "no_seg_output_flag", "vtk_mesh", "head_radius", "thresholding_flag"], "name": "Main Program Parameters"}, {"description": "Mutually exclusive options that specify variations on how BET should be run.", "mutually-exclusive": true, "id": "variational_params_group", "members": ["robust_iters_flag", "residual_optic_cleanup_flag", "reduce_bias_flag", "slice_padding_flag", "whole_set_mask_flag", "additional_surfaces_flag", "additional_surfaces_t2"], "name": "Variations on Default Functionality"}, {"description": "Optional miscellaneous parameters when running BET", "id": "miscellaneous_params_group", "members": ["verbose_flag", "debug_flag"], "name": "Miscellaneous Parameters"}], "outputfiles": [{"path-template": "[MASK].nii.gz", "description": "Main default mask output of BET", "optional": true, "id": "outfile", "name": "Output mask file"}, {"path-template": "[MASK]_mask.nii.gz", "description": "Binary mask file (from -m option)", "optional": true, "id": "binary_mask", "name": "Output binary mask file"}, {"path-template": "[MASK]_overlay.nii.gz", "description": "Overlaid brain surface onto original image", "optional": true, "id": "overlay_file", "name": "Surface overlay file"}, {"path-template": "[MASK]_skull.nii.gz", "description": "Approximate skull image file", "optional": true, "id": "approx_skull_img", "name": "Approximate skull file"}, {"path-template": "[MASK]_mesh.vtk", "description": "Mesh in VTK format", "optional": true, "id": "output_vtk_mesh", "name": "VTK mesh"}, {"path-template": "[MASK]_skull_mask.nii.gz", "description": "Output mask for skull image", "optional": true, "id": "skull_mask", "name": "Skull mask image"}, {"path-template": "[MASK]_inskull_mask.nii.gz", "description": "The in-skull mask file from betsurf (from -A or -A2)", "optional": true, "id": "out_inskull_mask", "name": "Output in-skull mask file"}, {"path-template": "[MASK]_inskull_mesh.nii.gz", "description": "The in-skull mesh file from betsurf (from -A or -A2)", "optional": true, "id": "out_inskull_mesh", "name": "Output in-skull mesh file"}, {"path-template": "[MASK]_inskull_mesh.off", "description": "The in-skull mesh .off file from betsurf (from -A or -A2)", "optional": true, "id": "out_inskull_off", "name": "Output in-skull mesh off file"}, {"path-template": "[MASK]_outskin_mask.nii.gz", "description": "The out-skin mask file from betsurf (from -A or -A2)", "optional": true, "id": "out_outskin_mask", "name": "Output out-skin mask file"}, {"path-template": "[MASK]_outskin_mesh.nii.gz", "description": "The out-skin mesh file from betsurf (from -A or -A2)", "optional": true, "id": "out_outskin_mesh", "name": "Output out-skin mesh file"}, {"path-template": "[MASK]_outskin_mesh.off", "description": "The out-skin mesh .off file from betsurf (from -A or -A2)", "optional": true, "id": "out_outskin_off", "name": "Output out-skin mesh off file"}, {"path-template": "[MASK]_outskull_mask.nii.gz", "description": "The out-skull mask file from betsurf (from -A or -A2)", "optional": true, "id": "out_outskull_mask", "name": "Output out-skull mask file"}, {"path-template": "[MASK]_outskull_mesh.nii.gz", "description": "The out-skull mesh file from betsurf (from -A or -A2)", "optional": true, "id": "out_outskull_mesh", "name": "Output out-skull mesh file"}, {"path-template": "[MASK]_outskull_mesh.off", "description": "The out-skull mesh .off file from betsurf (from -A or -A2)", "optional": true, "id": "out_outskull_off", "name": "Output out-skull mesh off file"}], "tests": [{"name": "fsl_bet_test", "invocation": {"infile": "sub-01_T1w.nii.gz", "maskfile": "img_bet"}, "assertions": {"exit-code": 0, "output-files": [{"id": "outfile", "md5-reference": "053507dd8605d62f5ba71dbecece17f8"}]}}], "ark_id": "https://n2t.net/ark:/70798/p7v861hg72s054fsp0", "platforms": [{"img": "/static/img/run_on_cbrain_green.png", "uri": "/cbrainredirect?cbrainurl=https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id%3D40"}]}, {"id": "zenodo.4472771", "title": "fslstats", "description": "Descriptor of fslstats from the FSL toolbox. Computes various statistics on nifti images.", "publicationdate": "2021-01-27", "deprecated": false, "downloads": 8011, "author": "Oxford Centre for Functional MRI of the Brain (FMRIB)", "version": "5.0.9", "doi": "10.5281/zenodo.4472771", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["neuroinformatics", "mri"], "toolbox": "FSL"}, "toolversion": "5.0.9", "descriptorurl": "https://github.com/aces/cbrain-plugins-neuro/blob/master/cbrain_task_descriptors/fsl_stats.json", "url": "https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/WhatsNew", "onlineplatformurls": ["https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id=175"], "commandline": "fslstats [t] [INPUT_FILE] [l] [u] [r] [R] [e] [E] [v] [V] [m] [M] [s] [S] [w] [x] [X] [c] [C] [p] [P] [a] [n] [k] [d] [h] [H] > [OUTPUT_FILE]", "containerimage": {"image": "mcin/docker-fsl:latest", "index": "docker://", "type": "singularity"}, "inputs": [{"id": "t", "name": "t", "optional": true, "type": "Flag", "value-key": "[t]", "description": "give a separate output line for each 3D volume of a 4D timeseries", "command-line-flag": "-t"}, {"id": "input_file", "name": "Input file", "optional": false, "type": "File", "value-key": "[INPUT_FILE]"}, {"id": "l", "name": "lower threshold", "optional": true, "type": "Number", "value-key": "[l]", "description": "set lower threshold", "command-line-flag": "-l"}, {"id": "u", "name": "upper threshold", "optional": true, "type": "Number", "value-key": "[u]", "description": "set upper threshold", "command-line-flag": "-u"}, {"id": "r", "name": "r", "optional": true, "type": "Flag", "value-key": "[r]", "description": " output <robust min intensity> <robust max intensity>", "command-line-flag": "-r"}, {"id": "R", "name": "R", "optional": true, "type": "Flag", "value-key": "[R]", "description": " output <min intensity> <max intensity>", "command-line-flag": "-R"}, {"id": "e", "name": "e", "optional": true, "type": "Flag", "value-key": "[e]", "description": " output mean entropy ; mean(-i*ln(i))", "command-line-flag": "-e"}, {"id": "E", "name": "E", "optional": true, "type": "Flag", "value-key": "[E]", "description": " output mean entropy (of nonzero voxels)", "command-line-flag": "-E"}, {"id": "v", "name": "v", "optional": true, "type": "Flag", "value-key": "[v]", "description": " output <voxels> <volume>", "command-line-flag": "-v"}, {"id": "V", "name": "V", "optional": true, "type": "Flag", "value-key": "[V]", "description": " output <voxels> <volume> (for nonzero voxels)", "command-line-flag": "-V"}, {"id": "m", "name": "m", "optional": true, "type": "Flag", "value-key": "[m]", "description": " output mean", "command-line-flag": "-m"}, {"id": "M", "name": "M", "optional": true, "type": "Flag", "value-key": "[M]", "description": " output mean (for nonzero voxels)", "command-line-flag": "-M"}, {"id": "s", "name": "s", "optional": true, "type": "Flag", "value-key": "[s]", "description": " output standard deviation", "command-line-flag": "-s"}, {"id": "S", "name": "S", "optional": true, "type": "Flag", "value-key": "[S]", "description": " output standard deviation (for nonzero voxels)", "command-line-flag": "-S"}, {"id": "w", "name": "w", "optional": true, "type": "Flag", "value-key": "[w]", "description": " output smallest ROI <xmin> <xsize> <ymin> <ysize> <zmin> <zsize> <tmin> <tsize> containing nonzero voxels", "command-line-flag": "-w"}, {"id": "x", "name": "x", "optional": true, "type": "Flag", "value-key": "[x]", "description": " output co-ordinates of maximum voxel", "command-line-flag": "-x"}, {"id": "X", "name": "X", "optional": true, "type": "Flag", "value-key": "[X]", "description": " output co-ordinates of minimum voxel", "command-line-flag": "-X"}, {"id": "c", "name": "c", "optional": true, "type": "Flag", "value-key": "[c]", "description": " output centre-of-gravity (cog) in mm coordinates", "command-line-flag": "-c"}, {"id": "C", "name": "C", "optional": true, "type": "Flag", "value-key": "[C]", "description": " output centre-of-gravity (cog) in voxel coordinates", "command-line-flag": "-C"}, {"id": "p", "name": "p", "optional": true, "type": "Number", "integer": true, "minimum": 0, "maximum": 100, "value-key": "[p]", "description": " output nth percentile (n between 0 and 100)", "command-line-flag": "-p"}, {"id": "P", "name": "P", "optional": true, "type": "Number", "integer": true, "minimum": 0, "maximum": 100, "value-key": "[P]", "description": " output nth percentile (for nonzero voxels)", "command-line-flag": "-P"}, {"id": "a", "name": "a", "optional": true, "type": "Flag", "value-key": "[a]", "description": " use absolute values of all image intensities", "command-line-flag": "-a"}, {"id": "n", "name": "n", "optional": true, "type": "Flag", "value-key": "[n]", "description": " treat NaN or Inf as zero for subsequent stats", "command-line-flag": "-n"}, {"id": "k", "name": "k", "optional": true, "type": "File", "value-key": "[k]", "description": " use the specified image (filename) for masking - overrides lower and upper thresholds", "command-line-flag": "-k"}, {"id": "d", "name": "d", "optional": true, "type": "File", "value-key": "[d]", "description": " take the difference between the base image and the image specified here", "command-line-flag": "-d"}, {"id": "h", "name": "h", "optional": true, "type": "Number", "integer": true, "value-key": "[h]", "description": " output a histogram (for the thresholded/masked voxels only) with nbins", "command-line-flag": "-h"}, {"id": "H", "name": "H", "optional": true, "type": "Number", "list": true, "min-list-entries": 3, "max-list-entries": 3, "list-separator": " ", "value-key": "[H]", "description": " output a histogram (for the thresholded/masked voxels only) with nbins and histogram limits of min and max", "command-line-flag": "-H"}], "groups": [{"one-is-required": true, "id": "output_type", "name": "output type", "members": ["r", "R", "e", "E", "v", "V", "m", "M", "s", "S", "w", "x", "X", "c", "C", "p", "P", "h", "H"]}], "name": "fslstats", "outputfiles": [{"id": "output", "name": "Output", "optional": false, "path-template": "[INPUT_FILE].txt", "value-key": "[OUTPUT_FILE]", "list": false, "path-template-stripped-extensions": [".nii.gz", ".nii"]}], "ark_id": "https://n2t.net/ark:/70798/p74x0p8km6r01371z7", "platforms": [{"img": "/static/img/run_on_cbrain_green.png", "uri": "/cbrainredirect?cbrainurl=https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id%3D175"}]}, {"id": "zenodo.2587160", "title": "makeblastdb", "description": "Application to create BLAST databases, version 2.7.1+", "publicationdate": "2019-03-07", "deprecated": false, "downloads": 7173, "author": "Altschul et al.", "version": "v2.7.1", "doi": "10.5281/zenodo.2587160", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["bioinformatics", "blast"]}, "toolversion": "v2.7.1", "commandline": "init_genpipes -a /tmp/$USER/cvmfs-cache -c /etc/parrot/ /cvmfs/soft.mugqic/CentOS6/software/blast/ncbi-blast-2.7.1+/bin/makeblastdb [IN] [INPUT_TYPE] [DBTYPE] [TITLE] [fPARSE_SEQIDS] [fHASHINDEX] [MASK_DATA_FILES] [MASK_ALGO_IDS] [MASK_DESC] [fGI_MASK] [GI_MASK_NAME] [OUT] [MAX_FILE_SIZE] [LOG_FILE] [TAX_ID] [TAX_ID_MAP]", "containerimage": {"index": "docker://", "image": "c3genomics/genpipes", "type": "singularity"}, "inputs": [{"command-line-flag": "-parse_seqids", "description": "A flag which enables parsing of sequence ids", "value-key": "[fPARSE_SEQIDS]", "optional": true, "type": "Flag", "id": "parse_seqids", "name": "Parse Sequence IDs flag"}, {"command-line-flag": "-hash_index", "description": "A flag which enables the creation of sequence hash values. These hash values can then be used to quickly determine if a given sequence data exists in this BLAST database.", "value-key": "[fHASHINDEX]", "optional": true, "type": "Flag", "id": "hash_index", "name": "Enable Hash indexes"}, {"command-line-flag": "-gi_mask", "description": "A flag which creates GI indexed masking data.", "value-key": "[fGI_MASK]", "optional": true, "requires-inputs": ["parse_seqids"], "type": "Flag", "id": "gi_mask", "name": "GI indexed masking data flag"}, {"command-line-flag": "-gi_mask_name", "description": "Comma-separated list of masking data output files.", "value-key": "[GI_MASK_NAME]", "type": "File", "list": true, "requires-inputs": ["mask_data", "gi_mask"], "list-separator": ",", "optional": true, "id": "gi_mask_name", "min-list-entries": 1, "name": "Masking data"}, {"command-line-flag": "-dbtype", "description": "Molecule type of target db", "value-key": "[DBTYPE]", "optional": false, "value-choices": ["nucl", "prot"], "type": "String", "id": "dbtype", "name": "Database Type"}, {"command-line-flag": "-in", "description": "The input source, either a file name or standard in (-, the default)", "value-key": "[IN]", "optional": true, "type": "File", "id": "in", "name": "Input file/database name"}, {"command-line-flag": "-out", "description": "   Name of BLAST database to be created\n   Default = input file name provided to -in argument\n   Required if multiple file(s)/database(s)\n   are provided as input", "value-key": "[OUT]", "optional": false, "type": "File", "id": "out", "name": "Name of BLAST database to be created"}, {"command-line-flag": "-input_type", "description": "Type of the data specified in input_file. Will default to 'fasta'", "value-key": "[INPUT_TYPE]", "optional": true, "value-choices": ["asn1_bin", "asn1_txt", "blastdb", "fasta"], "type": "String", "id": "input_type", "name": "Type of the data specified in input_file"}, {"command-line-flag": "-title", "description": "Title for BLAST database. Defaults to input file name.", "value-key": "[TITLE]", "optional": true, "type": "String", "id": "title", "name": "Title for BLAST database"}, {"command-line-flag": "-mask_data", "description": "Title for BLAST database. Defaults to input file name.", "value-key": "[MASK_DATA_FILES]", "type": "File", "list": true, "list-separator": ",", "optional": true, "id": "mask_data", "min-list-entries": 1, "name": "Title for BLAST database"}, {"command-line-flag": "-mask_id", "description": "Comma-separated list of strings to uniquely identify the masking algorithm.", "value-key": "[MASK_ALGO_IDS]", "type": "String", "list": true, "requires-inputs": ["mask_data"], "list-separator": ",", "disables-inputs": ["gi_mask"], "optional": true, "id": "mask_id", "min-list-entries": 1, "name": "Masking Algorithm"}, {"command-line-flag": "-mask_desc", "description": "Comma-separated list of free form strings to describe the masking algorithm details.", "value-key": "[MASK_DESC]", "type": "String", "list": true, "requires-inputs": ["mask_id"], "list-separator": ",", "optional": true, "id": "mask_desc", "min-list-entries": 1, "name": "Masking Algorithm Details"}, {"command-line-flag": "-max_file_sz", "description": "Maximum file size for BLAST database files.", "value-key": "[MAX_FILE_SIZE]", "optional": true, "type": "String", "id": "max_file_sz", "name": "Max database file size"}, {"command-line-flag": "-logfile", "description": "File to which the program log should be redirected.", "value-key": "[LOG_FILE]", "optional": true, "type": "File", "id": "logfile", "name": "Log file"}, {"command-line-flag": "-taxid", "description": "Taxonomy ID to assign to all sequences.", "value-key": "[TAX_ID]", "optional": true, "disables-inputs": ["taxid_map"], "minimum": 0, "type": "Number", "id": "taxid", "name": "Taxonomy ID"}, {"command-line-flag": "-taxid_map", "description": "Text file mapping sequence IDs to taxonomy IDs.", "value-key": "[TAX_ID_MAP]", "optional": true, "requires-inputs": ["parse_seqids"], "disables-inputs": ["taxid"], "type": "File", "id": "taxid_map", "name": "Sequence to taxonomy mapping"}], "outputfiles": [{"path-template": "[OUT].phr", "optional": false, "id": "outputdbphr", "name": "Output Database Headers"}, {"path-template": "[OUT].psq", "optional": false, "id": "outputdbpsq", "name": "Output Database Binary Sequences"}, {"path-template": "[OUT].pin", "optional": false, "id": "outputdbpin", "name": "Output Database Index File"}], "suggestedresources": {"walltime-estimate": 60, "ram": 1, "cpu-cores": 1}, "name": "makeblastdb", "ark_id": "https://n2t.net/ark:/70798/p7k6h7r6v3wdv4ts4f", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2602109", "title": "MCFLIRT", "description": "MCFLIRT, as implemented in Nipype (module: nipype.interfaces.fsl, interface: MCFLIRT).", "publicationdate": "2019-03-21", "deprecated": false, "downloads": 3947, "author": "Nipype (interface), Oxford Centre for Functional MRI of the Brain (FMRIB) (tool)", "version": "1.0.0", "doi": "10.5281/zenodo.2602109", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "mri"], "source": "nipype-interface"}, "name": "MCFLIRT", "commandline": "mcflirt [IN_FILE] [BINS] [COST] [DOF] [INIT] [INTERPOLATION] [MEAN_VOL] [OUT_FILE] [REF_FILE] [REF_VOL] [ROTATION] [SAVE_MATS] [SAVE_PLOTS] [SAVE_RMS] [SCALING] [SMOOTH] [STAGES] [STATS_IMGS] [USE_CONTOUR] [USE_GRADIENT]", "inputs": [{"id": "bins", "name": "Bins", "type": "Number", "integer": true, "value-key": "[BINS]", "command-line-flag": "-bins", "description": "An integer (int or long). Number of histogram bins.", "optional": true}, {"id": "cost", "name": "Cost", "type": "String", "value-key": "[COST]", "command-line-flag": "-cost", "description": "'mutualinfo' or 'woods' or 'corratio' or 'normcorr' or 'normmi' or 'leastsquares'. Cost function to optimize.", "optional": true, "value-choices": ["mutualinfo", "woods", "corratio", "normcorr", "normmi", "leastsquares"]}, {"id": "dof", "name": "Dof", "type": "Number", "integer": true, "value-key": "[DOF]", "command-line-flag": "-dof", "description": "An integer (int or long). Degrees of freedom for the transformation.", "optional": true}, {"id": "in_file", "name": "In file", "type": "File", "value-key": "[IN_FILE]", "command-line-flag": "-in", "description": "An existing file name. Timeseries to motion-correct.", "optional": false}, {"id": "init", "name": "Init", "type": "File", "value-key": "[INIT]", "command-line-flag": "-init", "description": "An existing file name. Inital transformation matrix.", "optional": true}, {"id": "interpolation", "name": "Interpolation", "type": "String", "value-key": "[INTERPOLATION]", "command-line-flag": "-", "command-line-flag-separator": "", "description": "'spline' or 'nn' or 'sinc'. Interpolation method for transformation.", "optional": true, "value-choices": ["spline_final", "nn_final", "sinc_final"]}, {"id": "mean_vol", "name": "Mean vol", "type": "Flag", "value-key": "[MEAN_VOL]", "command-line-flag": "-meanvol", "description": "A boolean. Register to mean volume.", "optional": true}, {"id": "out_file", "name": "Out file", "type": "File", "value-key": "[OUT_FILE]", "command-line-flag": "-out", "description": "A file name. File to write.", "optional": true}, {"id": "ref_file", "name": "Ref file", "type": "File", "value-key": "[REF_FILE]", "command-line-flag": "-reffile", "description": "An existing file name. Target image for motion correction.", "optional": true}, {"id": "ref_vol", "name": "Ref vol", "type": "Number", "integer": true, "value-key": "[REF_VOL]", "command-line-flag": "-refvol", "description": "An integer (int or long). Volume to align frames to.", "optional": true}, {"id": "rotation", "name": "Rotation", "type": "Number", "integer": true, "value-key": "[ROTATION]", "command-line-flag": "-rotation", "description": "An integer (int or long). Scaling factor for rotation tolerances.", "optional": true}, {"id": "save_mats", "name": "Save mats", "type": "Flag", "value-key": "[SAVE_MATS]", "command-line-flag": "-mats", "description": "A boolean. Save transformation matrices.", "optional": true}, {"id": "save_plots", "name": "Save plots", "type": "Flag", "value-key": "[SAVE_PLOTS]", "command-line-flag": "-plots", "description": "A boolean. Save transformation parameters.", "optional": true}, {"id": "save_rms", "name": "Save rms", "type": "Flag", "value-key": "[SAVE_RMS]", "command-line-flag": "-rmsabs -rmsrel", "description": "A boolean. Save rms displacement parameters.", "optional": true}, {"id": "scaling", "name": "Scaling", "type": "Number", "value-key": "[SCALING]", "command-line-flag": "-scaling", "description": "A float. Scaling factor to use.", "optional": true}, {"id": "smooth", "name": "Smooth", "type": "Number", "value-key": "[SMOOTH]", "command-line-flag": "-smooth", "description": "A float. Smoothing factor for the cost function.", "optional": true}, {"id": "stages", "name": "Stages", "type": "Number", "integer": true, "value-key": "[STAGES]", "command-line-flag": "-stages", "description": "An integer (int or long). Stages (if 4, perform final search with sinc interpolation.", "optional": true}, {"id": "stats_imgs", "name": "Stats imgs", "type": "Flag", "value-key": "[STATS_IMGS]", "command-line-flag": "-stats", "description": "A boolean. Produce variance and std. dev. images.", "optional": true}, {"id": "use_contour", "name": "Use contour", "type": "Flag", "value-key": "[USE_CONTOUR]", "command-line-flag": "-edge", "description": "A boolean. Run search on contour images.", "optional": true}, {"id": "use_gradient", "name": "Use gradient", "type": "Flag", "value-key": "[USE_GRADIENT]", "command-line-flag": "-gdt", "description": "A boolean. Run search on gradient images.", "optional": true}], "outputfiles": [{"name": "Mat file", "id": "mat_file", "path-template": "MAT_*", "optional": true, "description": "A list of items which are an existing file name. Transformation matrices.", "list": true}, {"name": "Mean img", "id": "mean_img", "path-template": "[OUT_FILE]_mean_reg.ext", "optional": true, "description": "An existing file name. Mean timeseries image (if mean_vol=true)."}, {"name": "Out file", "id": "out_file_outfile", "path-template": "[OUT_FILE]", "optional": true, "description": "An existing file name. Motion-corrected timeseries."}, {"name": "Par file", "id": "par_file", "path-template": "[OUT_FILE].par", "optional": true, "description": "An existing file name. Text-file with motion parameters."}, {"name": "Rms files", "id": "rms_files", "path-template": "[OUT_FILE]_*.rms", "optional": true, "description": "A list of items which are an existing file name. Absolute and relative displacement parameters.", "list": true}, {"name": "Std img", "id": "std_img", "path-template": "[OUT_FILE]_sigma.ext", "optional": true, "description": "An existing file name. Standard deviation image."}, {"name": "Variance img", "id": "variance_img", "path-template": "[OUT_FILE]_variance.ext", "optional": true, "description": "An existing file name. Variance image."}], "toolversion": "1.0.0", "containerimage": {"image": "mcin/docker-fsl:latest", "type": "docker", "index": "index.docker.io"}, "url": "https://github.com/nipy/nipype/blob/master/nipype/interfaces/fsl/preprocess.py", "ark_id": "https://n2t.net/ark:/70798/p7tt53wjk9bzz8wgdd", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2601876", "title": "DTIFit", "description": "DTIFit, as implemented in Nipype (module: nipype.interfaces.fsl, interface: DTIFit).", "publicationdate": "2019-03-21", "deprecated": false, "downloads": 3874, "author": "Nipype (interface), Oxford Centre for Functional MRI of the Brain (FMRIB) (tool)", "version": "1.0.0", "doi": "10.5281/zenodo.2601876", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "dmri"], "source": "nipype-interface"}, "name": "DTIFit", "commandline": "dtifit [DWI] [BASE_NAME] [MASK] [BVECS] [BVALS] [CNI] [GRADNONLIN] [LITTLE_BIT] [MAX_X] [MAX_Y] [MAX_Z] [MIN_X] [MIN_Y] [MIN_Z] [SAVE_TENSOR] [SSE]", "inputs": [{"id": "base_name", "name": "Base name", "type": "String", "value-key": "[BASE_NAME]", "command-line-flag": "-o", "description": "A unicode string. Base_name that all output files will start with.", "optional": true, "default-value": "dtifit_"}, {"id": "bvals", "name": "Bvals", "type": "File", "value-key": "[BVALS]", "command-line-flag": "-b", "description": "An existing file name. B values file.", "optional": false}, {"id": "bvecs", "name": "Bvecs", "type": "File", "value-key": "[BVECS]", "command-line-flag": "-r", "description": "An existing file name. B vectors file.", "optional": false}, {"id": "cni", "name": "Cni", "type": "File", "value-key": "[CNI]", "command-line-flag": "--cni", "command-line-flag-separator": "=", "description": "An existing file name. Input confound regressors.", "optional": true}, {"id": "dwi", "name": "Dwi", "type": "File", "value-key": "[DWI]", "command-line-flag": "-k", "description": "An existing file name. Diffusion weighted image data file.", "optional": false}, {"id": "gradnonlin", "name": "Gradnonlin", "type": "File", "value-key": "[GRADNONLIN]", "command-line-flag": "--gradnonlin", "command-line-flag-separator": "=", "description": "An existing file name. Gradient non linearities.", "optional": true}, {"id": "little_bit", "name": "Little bit", "type": "Flag", "value-key": "[LITTLE_BIT]", "command-line-flag": "--littlebit", "description": "A boolean. Only process small area of brain.", "optional": true}, {"id": "mask", "name": "Mask", "type": "File", "value-key": "[MASK]", "command-line-flag": "-m", "description": "An existing file name. Bet binary mask file.", "optional": false}, {"id": "max_x", "name": "Max x", "type": "Number", "integer": true, "value-key": "[MAX_X]", "command-line-flag": "-X", "description": "An integer (int or long). Max x.", "optional": true}, {"id": "max_y", "name": "Max y", "type": "Number", "integer": true, "value-key": "[MAX_Y]", "command-line-flag": "-Y", "description": "An integer (int or long). Max y.", "optional": true}, {"id": "max_z", "name": "Max z", "type": "Number", "integer": true, "value-key": "[MAX_Z]", "command-line-flag": "-Z", "description": "An integer (int or long). Max z.", "optional": true}, {"id": "min_x", "name": "Min x", "type": "Number", "integer": true, "value-key": "[MIN_X]", "command-line-flag": "-x", "description": "An integer (int or long). Min x.", "optional": true}, {"id": "min_y", "name": "Min y", "type": "Number", "integer": true, "value-key": "[MIN_Y]", "command-line-flag": "-y", "description": "An integer (int or long). Min y.", "optional": true}, {"id": "min_z", "name": "Min z", "type": "Number", "integer": true, "value-key": "[MIN_Z]", "command-line-flag": "-z", "description": "An integer (int or long). Min z.", "optional": true}, {"id": "save_tensor", "name": "Save tensor", "type": "Flag", "value-key": "[SAVE_TENSOR]", "command-line-flag": "--save_tensor", "description": "A boolean. Save the elements of the tensor.", "optional": true}, {"id": "sse", "name": "Sse", "type": "Flag", "value-key": "[SSE]", "command-line-flag": "--sse", "description": "A boolean. Output sum of squared errors.", "optional": true}], "outputfiles": [{"name": "Fa", "id": "FA", "path-template": "dtifit__FA.nii", "optional": true, "description": "An existing file name. Path/name of file with the fractional anisotropy."}, {"name": "L1", "id": "L1", "path-template": "dtifit__L1.nii", "optional": true, "description": "An existing file name. Path/name of file with the 1st eigenvalue."}, {"name": "L2", "id": "L2", "path-template": "dtifit__L2.nii", "optional": true, "description": "An existing file name. Path/name of file with the 2nd eigenvalue."}, {"name": "L3", "id": "L3", "path-template": "dtifit__L3.nii", "optional": true, "description": "An existing file name. Path/name of file with the 3rd eigenvalue."}, {"name": "Md", "id": "MD", "path-template": "dtifit__MD.nii", "optional": true, "description": "An existing file name. Path/name of file with the mean diffusivity."}, {"name": "Mo", "id": "MO", "path-template": "dtifit__MO.nii", "optional": true, "description": "An existing file name. Path/name of file with the mode of anisotropy."}, {"name": "S0", "id": "S0", "path-template": "dtifit__S0.nii", "optional": true, "description": "An existing file name. Path/name of file with the raw t2 signal with no diffusion weighting."}, {"name": "V1", "id": "V1", "path-template": "dtifit__V1.nii", "optional": true, "description": "An existing file name. Path/name of file with the 1st eigenvector."}, {"name": "V2", "id": "V2", "path-template": "dtifit__V2.nii", "optional": true, "description": "An existing file name. Path/name of file with the 2nd eigenvector."}, {"name": "V3", "id": "V3", "path-template": "dtifit__V3.nii", "optional": true, "description": "An existing file name. Path/name of file with the 3rd eigenvector."}, {"name": "Sse", "id": "sse_outfile", "path-template": "dtifit__sse.nii", "optional": true, "description": "An existing file name. Path/name of file with the summed squared error."}, {"name": "Tensor", "id": "tensor", "path-template": "dtifit__tensor.nii", "optional": true, "description": "An existing file name. Path/name of file with the 4d tensor volume."}], "toolversion": "1.0.0", "containerimage": {"image": "mcin/docker-fsl:latest", "type": "docker", "index": "index.docker.io"}, "url": "https://github.com/nipy/nipype/blob/master/nipype/interfaces/fsl/dti.py", "ark_id": "https://n2t.net/ark:/70798/p7qbt0sqt9xh42zzbt", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.1450991", "title": "fsl_probtrackx2", "description": "probabilistic tracking with crossing fibres", "publicationdate": "2018-10-08", "deprecated": false, "downloads": 3867, "author": "Oxford Centre for Functional MRI of the Brain (FMRIB)", "version": "1.0.0", "doi": "10.5281/zenodo.1450991", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "dmri"]}, "toolversion": "1.0.0", "name": "fsl_probtrackx2", "descriptorurl": "https://github.com/aces/cbrain-plugins-neuro/blob/master/cbrain_task_descriptors/fsl_probtrackx2.json", "commandline": "cp -rL [INPUT_DIR] [OUTPUT_DIR]; probtrackx2 -s [OUTPUT_DIR]/[BASENAME] -m [OUTPUT_DIR]/[MASKNAME] -x [SEEDFILE] --dir=[OUTPUT_DIR]/[FINALDIR] [FORCEDIR] [OPD] [PD] [OS2T] --targetmasks=[TARGETMASKS] --xfm=[OUTPUT_DIR]/[XFM] --invxfm=[OUTPUT_DIR]/[INVXFM]", "inputs": [{"description": "A bedpostX directory", "value-key": "[INPUT_DIR]", "type": "File", "optional": false, "id": "inputdir", "name": "Input Directory"}, {"description": "Basename for samples files - e.g. 'merged'", "value-key": "[BASENAME]", "type": "String", "optional": false, "id": "basename", "name": "Base name"}, {"description": "Bet binary mask file in diffusion space", "value-key": "[MASKNAME]", "type": "String", "optional": false, "id": "maskname", "name": "Mask name"}, {"description": "Seed volume or list (ascii text file) of volumes and/or surfaces", "value-key": "[SEEDFILE]", "type": "File", "optional": false, "id": "seedfile", "name": "Seed file"}, {"description": "Directory to put the final volumes in - code makes this directory - default='logdir'", "value-key": "[FINALDIR]", "type": "String", "optional": false, "id": "finaldir", "name": "Directory to put the final volumes in"}, {"command-line-flag": "--forcedir", "description": "Use the actual directory name given - i.e. don't add + to make a new directory", "default-value": true, "value-key": "[FORCEDIR]", "optional": true, "type": "Flag", "id": "forcedir", "name": "Use the actual directory name given"}, {"command-line-flag": "--opd", "description": "Output path distribution", "default-value": true, "value-key": "[OPD]", "optional": true, "type": "Flag", "id": "outputpath", "name": "Output path"}, {"command-line-flag": "--pd", "description": "Correct path distribution for the length of the pathways", "default-value": true, "value-key": "[PD]", "optional": true, "type": "Flag", "id": "pathdistribution", "name": "Correct path distribution"}, {"command-line-flag": "--os2t", "description": "Output seeds to targets", "default-value": true, "value-key": "[OS2T]", "optional": true, "type": "Flag", "id": "outseeds", "name": "Output seeds"}, {"description": "File containing a list of target masks - for seeds_to_targets classification", "value-key": "[TARGETMASKS]", "type": "File", "optional": false, "id": "targetmasks", "name": "File containing a list of target masks"}, {"description": "Transform taking seed space to DTI space (either FLIRT matrix or FNIRT warpfield) - default is identity", "value-key": "[XFM]", "type": "String", "optional": false, "id": "xfm", "name": "Transform taking seed space to DTI space"}, {"description": "Transform taking DTI space to seed space (compulsory when using a warpfield for seeds_to_dti)", "value-key": "[INVXFM]", "type": "String", "optional": false, "id": "infxfm", "name": "Transform taking DTI space to seed space"}, {"description": "Output directory name.", "default-value": "probtrackx2_output", "value-key": "[OUTPUT_DIR]", "type": "String", "list": false, "optional": false, "id": "outdir", "name": "Output directory"}], "containerimage": {"index": "index.docker.io", "image": "mcin/docker-fsl:latest", "type": "docker"}, "outputfiles": [{"description": "A folder containing the output result.", "list": false, "id": "folder_out", "optional": false, "path-template": "[OUTPUT_DIR]", "name": "Output folder"}], "suggestedresources": {"walltime-estimate": 331200}, "ark_id": "https://n2t.net/ark:/70798/p75964z0p20sp7js7q", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.1494312", "title": "fsl_first", "description": "FIRST is a model-based segmentation and registration tool, based on a Bayesian model of shape and appearance for subcortical structures.", "publicationdate": "2018-11-22", "deprecated": false, "downloads": 3852, "author": "Oxford Centre for Functional MRI of the Brain (FMRIB)", "version": "5.0.0", "doi": "10.5281/zenodo.1494312", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "mri"]}, "toolversion": "5.0.0", "name": "fsl_first", "descriptorurl": "https://github.com/aces/cbrain-plugins-neuro/blob/master/cbrain_task_descriptors/fsl_first.json", "commandline": "mkdir -p [OUTPUT_DIR]; run_first_all [METHOD] [BRAIN_EXTRACTED] [SPECIFIED_STRUCTURE] [AFFINE] [THREE_STAGE] [VERBOSE] [INPUT_FILE] -o [OUTPUT_DIR]/[PREFIX]", "containerimage": {"image": "mcin/docker-fsl:latest", "index": "index.docker.io", "type": "docker"}, "inputs": [{"command-line-flag": "-m", "description": "Method must be one of 'auto' (default), 'fast', 'none', or it can be a numerical threshold value. This specifies the boundary correction method. Auto chooses different options for different structures using the settings that were found to be empirically optimal for each structure. Other options use: fast (using FAST-based, mixture-model, tissue-type classification) or threshold (thresholds a simple single-Gaussian intensity model).", "value-key": "[METHOD]", "type": "String", "list": false, "optional": true, "id": "method", "name": "Method"}, {"command-line-flag": "-i", "description": "Input image file (e.g. img.nii.gz).", "value-key": "[INPUT_FILE]", "type": "File", "list": false, "optional": false, "id": "input_file", "name": "Input file"}, {"command-line-flag": "-b", "description": "Whether the input is already brain extracted.", "value-key": "[BRAIN_EXTRACTED]", "type": "Flag", "list": false, "optional": true, "id": "brain_extracted", "name": "Brain extracted"}, {"command-line-flag": "-s", "description": "Run only on one specified structure (e.g. L_Hipp) or a comma-separated list (no spaces). Choose from: 'L_Hipp', 'R_Hipp', 'L_Accu', 'R_Accu', 'L_Amyg', 'R_Amyg', 'L_Caud', 'R_Caud', 'L_Pall', 'R_Pall', 'L_Puta', 'R_Puta', 'L_Thal', 'R_Thal', 'BrStem'.", "value-key": "[SPECIFIED_STRUCTURE]", "type": "String", "list": false, "optional": true, "id": "specified_structure", "name": "Specify structure"}, {"command-line-flag": "-a", "description": "Use affine matrix (i.e. do not re-run registration).", "value-key": "[AFFINE]", "type": "File", "list": false, "optional": true, "id": "affine", "name": "Use Affine Matrix"}, {"command-line-flag": "-3", "description": "Use 3-stage affine registration. Only currently implemented for the hippocampus.", "value-key": "[THREE_STAGE]", "type": "Flag", "list": false, "optional": true, "id": "three_stage", "name": "Three stage registration"}, {"command-line-flag": "-v", "description": "Verbose output.", "value-key": "[VERBOSE]", "type": "Flag", "list": false, "optional": true, "id": "verbose", "name": "Verbose"}, {"description": "Prefix for each files in the directory output.", "value-key": "[PREFIX]", "type": "String", "optional": false, "list": false, "default-value": "output", "id": "prefix", "name": "Prefix"}], "outputfiles": [{"id": "outputs", "name": "First Outputs", "description": "Output directory of First", "value-key": "[OUTPUT_DIR]", "path-template": "[INPUT_FILE]", "list": false, "path-template-stripped-extensions": [".nii.gz", ".nii"]}, {"id": "std_sub_outputs", "name": "Registered outputs", "description": "Std sub output", "path-template": "[INPUT_FILE]_to_std_sub*", "list": true, "path-template-stripped-extensions": [".nii.gz", ".nii"]}], "tests": [{"name": "fsl_first_test", "invocation": {"input_file": "sub-01_T1w.nii.gz", "prefix": "img_first"}, "assertions": {"exit-code": 0, "output-files": [{"id": "outputs"}]}}], "ark_id": "https://n2t.net/ark:/70798/p72kbbrd79ndn1qbhd", "platforms": [{"img": "/static/img/run_on_cbrain_green.png", "uri": "/cbrainredirect?cbrainurl=https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id%3D51"}]}, {"id": "zenodo.2566455", "title": "BIDS App - FSL Diffusion Preprocessing", "description": "Preprocessing pipeline for diffusion MRI data using the FSL software suite.", "publicationdate": "2019-02-15", "deprecated": false, "downloads": 3847, "author": "Greg Kiar, using FSL from FMRIB at Oxford", "version": "5.0.9", "doi": "10.5281/zenodo.2566455", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "diffusion MRI", "dwi"]}, "commandline": "python3 /opt/preprocessing_pipeline.py [BIDS_DIR] [OUTPUT_DIR] [ANALYSIS_LEVEL] [PARTICIPANT_LABEL] [SESSION_LABEL] [VERBOSE] [BOUTIQUES] [GPU] [FSLDIR] [PARCELLATION]", "containerimage": {"image": "gkiar/dwipreproc_fsl-5.0.11_minified", "index": "docker.io", "type": "docker"}, "inputs": [{"description": "Directory to a BIDS-organized dataset.", "id": "bids_dir", "name": "bids_dir", "optional": false, "type": "String", "value-key": "[BIDS_DIR]"}, {"description": "Directory to store the preprocessed derivatives.", "id": "output_dir", "name": "output_dir", "optional": false, "type": "String", "value-key": "[OUTPUT_DIR]"}, {"description": "Level of analysis to perform. Options: session", "id": "analysis_level", "name": "analysis_level", "optional": false, "type": "String", "value-choices": ["session"], "value-key": "[ANALYSIS_LEVEL]"}, {"command-line-flag": "--participant_label", "description": "Label of the participant(s) to process, omitting the 'sub-' portion of the directory name. Supplying none means the entire dataset will be processed.", "id": "participant_label", "name": "participant_label", "optional": true, "type": "String", "value-key": "[PARTICIPANT_LABEL]"}, {"command-line-flag": "--session_label", "description": "Label of the session(s) to process, omitting the 'ses-' portion of the directory name. Supplying none means the entire dataset will be processed.", "id": "session_label", "name": "session_label", "optional": true, "type": "String", "value-key": "[SESSION_LABEL]"}, {"command-line-flag": "--verbose", "description": "Flag toggling verbose output statements.", "id": "verbose", "name": "verbose", "optional": true, "type": "Flag", "value-key": "[VERBOSE]"}, {"command-line-flag": "--boutiques", "description": "Flag toggling descriptor creation.", "id": "boutiques", "name": "boutiques", "optional": true, "type": "Flag", "value-key": "[BOUTIQUES]"}, {"command-line-flag": "--gpu", "description": "Toggles using GPU accelerated eddy.", "id": "gpu", "name": "gpu", "optional": true, "type": "Flag", "value-key": "[GPU]"}, {"command-line-flag": "--fsldir", "default-value": "/usr/share/fsl/", "description": "Path to local installation of FSL. Defaults to /usr/share/fsl/.", "id": "fsldir", "name": "fsldir", "optional": true, "type": "String", "value-key": "[FSLDIR]"}, {"command-line-flag": "--parcellation", "description": "Parcellation/Label volumes which will be transformed into the subject/session DWI space.", "id": "parcellation", "list": true, "name": "parcellation", "optional": true, "type": "String", "value-key": "[PARCELLATION]"}], "name": "BIDS App - FSL Diffusion Preprocessing", "outputfiles": [{"description": "Directory to store the preprocessed derivatives.", "id": "output_dir_path", "name": "Output directory", "optional": false, "path-template": "[OUTPUT_DIR]"}], "suggestedresources": {"cpu-cores": 1, "ram": 8, "walltime-estimate": 10800}, "toolversion": "5.0.9", "ark_id": "https://n2t.net/ark:/70798/p7c97zsxr6v1c0n7w9", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2597643", "title": "FLIRT", "description": "FLIRT, as implemented in Nipype (module: nipype.interfaces.fsl, interface: FLIRT).", "publicationdate": "2019-03-18", "deprecated": false, "downloads": 3846, "author": "Nipype (interface), Oxford Centre for Functional MRI of the Brain (FMRIB) (tool)", "version": "1.0.0", "doi": "10.5281/zenodo.2597643", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "fmri"], "source": "nipype-interface"}, "name": "FLIRT", "commandline": "flirt [ANGLE_REP] [APPLY_ISOXFM] [APPLY_XFM] [BBRSLOPE] [BBRTYPE] [BGVALUE] [BINS] [COARSE_SEARCH] [COST] [COST_FUNC] [DATATYPE] [DOF] [ECHOSPACING] [FIELDMAP] [FIELDMAPMASK] [FINE_SEARCH] [FORCE_SCALING] [IN_FILE] [IN_MATRIX_FILE] [IN_WEIGHT] [INTERP] [MIN_SAMPLING] [NO_CLAMP] [NO_RESAMPLE] [NO_RESAMPLE_BLUR] [NO_SEARCH] [PADDING_SIZE] [PEDIR] [REF_WEIGHT] [REFERENCE] [RIGID2D] [SCHEDULE] [SEARCHR_X] [SEARCHR_Y] [SEARCHR_Z] [SINC_WIDTH] [SINC_WINDOW] [USES_QFORM] [VERBOSE] [WM_SEG] [WMCOORDS] [WMNORMS] [OUT_FILE] [OUT_MATRIX_FILE]", "inputs": [{"id": "angle_rep", "name": "Angle rep", "type": "String", "value-key": "[ANGLE_REP]", "command-line-flag": "-anglerep", "description": "'quaternion' or 'euler'. Representation of rotation angles.", "optional": true, "value-choices": ["quaternion", "euler"]}, {"id": "apply_isoxfm", "name": "Apply isoxfm", "type": "Number", "value-key": "[APPLY_ISOXFM]", "command-line-flag": "-applyisoxfm", "description": "A float. As applyxfm but forces isotropic resampling.", "optional": true}, {"id": "apply_xfm", "name": "Apply xfm", "type": "Flag", "value-key": "[APPLY_XFM]", "command-line-flag": "-applyxfm", "description": "A boolean. Apply transformation supplied by in_matrix_file or uses_qform to use the affine matrix stored in the reference header.", "optional": true}, {"id": "bbrslope", "name": "Bbrslope", "type": "Number", "value-key": "[BBRSLOPE]", "command-line-flag": "-bbrslope", "description": "A float. Value of bbr slope.", "optional": true}, {"id": "bbrtype", "name": "Bbrtype", "type": "String", "value-key": "[BBRTYPE]", "command-line-flag": "-bbrtype", "description": "'signed' or 'global_abs' or 'local_abs'. Type of bbr cost function: signed [default], global_abs, local_abs.", "optional": true, "value-choices": ["signed", "global_abs", "local_abs"]}, {"id": "bgvalue", "name": "Bgvalue", "type": "Number", "value-key": "[BGVALUE]", "command-line-flag": "-setbackground", "description": "A float. Use specified background value for points outside fov.", "optional": true}, {"id": "bins", "name": "Bins", "type": "Number", "integer": true, "value-key": "[BINS]", "command-line-flag": "-bins", "description": "An integer (int or long). Number of histogram bins.", "optional": true}, {"id": "coarse_search", "name": "Coarse search", "type": "Number", "integer": true, "value-key": "[COARSE_SEARCH]", "command-line-flag": "-coarsesearch", "description": "An integer (int or long). Coarse search delta angle.", "optional": true}, {"id": "cost", "name": "Cost", "type": "String", "value-key": "[COST]", "command-line-flag": "-cost", "description": "'mutualinfo' or 'corratio' or 'normcorr' or 'normmi' or 'leastsq' or 'labeldiff' or 'bbr'. Cost function.", "optional": true, "value-choices": ["mutualinfo", "corratio", "normcorr", "normmi", "leastsq", "labeldiff", "bbr"]}, {"id": "cost_func", "name": "Cost func", "type": "String", "value-key": "[COST_FUNC]", "command-line-flag": "-searchcost", "description": "'mutualinfo' or 'corratio' or 'normcorr' or 'normmi' or 'leastsq' or 'labeldiff' or 'bbr'. Cost function.", "optional": true, "value-choices": ["mutualinfo", "corratio", "normcorr", "normmi", "leastsq", "labeldiff", "bbr"]}, {"id": "datatype", "name": "Datatype", "type": "String", "value-key": "[DATATYPE]", "command-line-flag": "-datatype", "description": "'char' or 'short' or 'int' or 'float' or 'double'. Force output data type.", "optional": true, "value-choices": ["char", "short", "int", "float", "double"]}, {"id": "dof", "name": "Dof", "type": "Number", "integer": true, "value-key": "[DOF]", "command-line-flag": "-dof", "description": "An integer (int or long). Number of transform degrees of freedom.", "optional": true}, {"id": "echospacing", "name": "Echospacing", "type": "Number", "value-key": "[ECHOSPACING]", "command-line-flag": "-echospacing", "description": "A float. Value of epi echo spacing - units of seconds.", "optional": true}, {"id": "fieldmap", "name": "Fieldmap", "type": "File", "value-key": "[FIELDMAP]", "command-line-flag": "-fieldmap", "description": "A file name. Fieldmap image in rads/s - must be already registered to the reference image.", "optional": true}, {"id": "fieldmapmask", "name": "Fieldmapmask", "type": "File", "value-key": "[FIELDMAPMASK]", "command-line-flag": "-fieldmapmask", "description": "A file name. Mask for fieldmap image.", "optional": true}, {"id": "fine_search", "name": "Fine search", "type": "Number", "integer": true, "value-key": "[FINE_SEARCH]", "command-line-flag": "-finesearch", "description": "An integer (int or long). Fine search delta angle.", "optional": true}, {"id": "force_scaling", "name": "Force scaling", "type": "Flag", "value-key": "[FORCE_SCALING]", "command-line-flag": "-forcescaling", "description": "A boolean. Force rescaling even for low-res images.", "optional": true}, {"id": "in_file", "name": "In file", "type": "File", "value-key": "[IN_FILE]", "command-line-flag": "-in", "description": "An existing file name. Input file.", "optional": false}, {"id": "in_matrix_file", "name": "In matrix file", "type": "File", "value-key": "[IN_MATRIX_FILE]", "command-line-flag": "-init", "description": "A file name. Input 4x4 affine matrix.", "optional": true}, {"id": "in_weight", "name": "In weight", "type": "File", "value-key": "[IN_WEIGHT]", "command-line-flag": "-inweight", "description": "An existing file name. File for input weighting volume.", "optional": true}, {"id": "interp", "name": "Interp", "type": "String", "value-key": "[INTERP]", "command-line-flag": "-interp", "description": "'trilinear' or 'nearestneighbour' or 'sinc' or 'spline'. Final interpolation method used in reslicing.", "optional": true, "value-choices": ["trilinear", "nearestneighbour", "sinc", "spline"]}, {"id": "min_sampling", "name": "Min sampling", "type": "Number", "value-key": "[MIN_SAMPLING]", "command-line-flag": "-minsampling", "description": "A float. Set minimum voxel dimension for sampling.", "optional": true}, {"id": "no_clamp", "name": "No clamp", "type": "Flag", "value-key": "[NO_CLAMP]", "command-line-flag": "-noclamp", "description": "A boolean. Do not use intensity clamping.", "optional": true}, {"id": "no_resample", "name": "No resample", "type": "Flag", "value-key": "[NO_RESAMPLE]", "command-line-flag": "-noresample", "description": "A boolean. Do not change input sampling.", "optional": true}, {"id": "no_resample_blur", "name": "No resample blur", "type": "Flag", "value-key": "[NO_RESAMPLE_BLUR]", "command-line-flag": "-noresampblur", "description": "A boolean. Do not use blurring on downsampling.", "optional": true}, {"id": "no_search", "name": "No search", "type": "Flag", "value-key": "[NO_SEARCH]", "command-line-flag": "-nosearch", "description": "A boolean. Set all angular searches to ranges 0 to 0.", "optional": true}, {"id": "padding_size", "name": "Padding size", "type": "Number", "integer": true, "value-key": "[PADDING_SIZE]", "command-line-flag": "-paddingsize", "description": "An integer (int or long). For applyxfm: interpolates outside image by size.", "optional": true}, {"id": "pedir", "name": "Pedir", "type": "Number", "integer": true, "value-key": "[PEDIR]", "command-line-flag": "-pedir", "description": "An integer (int or long). Phase encode direction of epi - 1/2/3=x/y/z & -1/-2/-3=-x/-y/-z.", "optional": true}, {"id": "ref_weight", "name": "Ref weight", "type": "File", "value-key": "[REF_WEIGHT]", "command-line-flag": "-refweight", "description": "An existing file name. File for reference weighting volume.", "optional": true}, {"id": "reference", "name": "Reference", "type": "File", "value-key": "[REFERENCE]", "command-line-flag": "-ref", "description": "An existing file name. Reference file.", "optional": false}, {"id": "rigid2D", "name": "Rigid2d", "type": "Flag", "value-key": "[RIGID2D]", "command-line-flag": "-2D", "description": "A boolean. Use 2d rigid body mode - ignores dof.", "optional": true}, {"id": "schedule", "name": "Schedule", "type": "File", "value-key": "[SCHEDULE]", "command-line-flag": "-schedule", "description": "An existing file name. Replaces default schedule.", "optional": true}, {"id": "searchr_x", "name": "Searchr x", "type": "Number", "list": true, "integer": true, "min-list-entries": 2, "max-list-entries": 2, "value-key": "[SEARCHR_X]", "command-line-flag": "-searchrx", "description": "A list of from 2 to 2 items which are an integer (int or long). Search angles along x-axis, in degrees.", "optional": true}, {"id": "searchr_y", "name": "Searchr y", "type": "Number", "list": true, "integer": true, "min-list-entries": 2, "max-list-entries": 2, "value-key": "[SEARCHR_Y]", "command-line-flag": "-searchry", "description": "A list of from 2 to 2 items which are an integer (int or long). Search angles along y-axis, in degrees.", "optional": true}, {"id": "searchr_z", "name": "Searchr z", "type": "Number", "list": true, "integer": true, "min-list-entries": 2, "max-list-entries": 2, "value-key": "[SEARCHR_Z]", "command-line-flag": "-searchrz", "description": "A list of from 2 to 2 items which are an integer (int or long). Search angles along z-axis, in degrees.", "optional": true}, {"id": "sinc_width", "name": "Sinc width", "type": "Number", "integer": true, "value-key": "[SINC_WIDTH]", "command-line-flag": "-sincwidth", "description": "An integer (int or long). Full-width in voxels.", "optional": true}, {"id": "sinc_window", "name": "Sinc window", "type": "String", "value-key": "[SINC_WINDOW]", "command-line-flag": "-sincwindow", "description": "'rectangular' or 'hanning' or 'blackman'. Sinc window.", "optional": true, "value-choices": ["rectangular", "hanning", "blackman"]}, {"id": "uses_qform", "name": "Uses qform", "type": "Flag", "value-key": "[USES_QFORM]", "command-line-flag": "-usesqform", "description": "A boolean. Initialize using sform or qform.", "optional": true}, {"id": "verbose", "name": "Verbose", "type": "Number", "integer": true, "value-key": "[VERBOSE]", "command-line-flag": "-verbose", "description": "An integer (int or long). Verbose mode, 0 is least.", "optional": true}, {"id": "wm_seg", "name": "Wm seg", "type": "File", "value-key": "[WM_SEG]", "command-line-flag": "-wmseg", "description": "A file name. White matter segmentation volume needed by bbr cost function.", "optional": true}, {"id": "wmcoords", "name": "Wmcoords", "type": "File", "value-key": "[WMCOORDS]", "command-line-flag": "-wmcoords", "description": "A file name. White matter boundary coordinates for bbr cost function.", "optional": true}, {"id": "wmnorms", "name": "Wmnorms", "type": "File", "value-key": "[WMNORMS]", "command-line-flag": "-wmnorms", "description": "A file name. White matter boundary normals for bbr cost function.", "optional": true}], "outputfiles": [{"name": "Out file", "id": "out_file", "path-template": "[IN_FILE]_flirt", "path-template-stripped-extensions": [".nii.gz", ".nii"], "optional": true, "description": "An existing file name. Path/name of registered file (if generated).", "value-key": "[OUT_FILE]", "command-line-flag": "-out"}, {"name": "Out matrix file", "id": "out_matrix_file", "path-template": "[IN_FILE]_flirt.mat", "path-template-stripped-extensions": [".nii.gz", ".nii"], "optional": true, "description": "An existing file name. Path/name of calculated affine transform (if generated).", "value-key": "[OUT_MATRIX_FILE]", "command-line-flag": "-omat"}], "groups": [{"id": "mutex_group", "name": "Mutex group", "members": ["apply_xfm", "apply_isoxfm"], "mutually-exclusive": true}], "toolversion": "1.0.0", "containerimage": {"image": "mcin/docker-fsl:latest", "type": "docker", "index": "index.docker.io"}, "ark_id": "https://n2t.net/ark:/70798/p7w1tt2vr4hrq4wrx7", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.1494308", "title": "fsl_fast", "description": "FAST (FMRIB's Automated Segmentation Tool) segments a 3D image of the brain into different tissue types (Grey Matter, White Matter, CSF, etc.), whilst also correcting for spatial intensity variations (also known as bias field or RF inhomogeneities), via a hidden Markov random field model and an associated EM algorithm. Note that the alternative priors option is not supported at this time.", "publicationdate": "2018-11-22", "deprecated": false, "downloads": 3821, "author": "Oxford Centre for Functional MRI of the Brain (FMRIB)", "version": "5.0.0", "doi": "10.5281/zenodo.1494308", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "mri"]}, "toolversion": "5.0.0", "name": "fsl_fast", "descriptorurl": "https://github.com/aces/cbrain-plugins-neuro/blob/master/cbrain_task_descriptors/fsl_fast.json", "commandline": "fast [NUM_CLASSES] [LOOP_ITERS] [BF_SMOOTHING] [IMG_TYPE] [INIT_SEG_SMOOTHNESS] [BINARY_SEGMENTS] [PRIOR_INIT] [NO_PVE] [BIAS_FIELD] [BIAS_CORR_IMG] [NO_BIAS_RM] [OUTPUT_BASENAME] [PRIORS_THROUGHOUT] [SEG_INIT_ITERS] [MIXEL_SMOOTHNESS] [NUM_MAIN_LOOP_ITERS] [HYPER_SEG_SMOOTHNESS] [VERBOSE] [MANUAL_INTENSITIES_FILE] [OUTPUT_PROB_MAPS] [IN_FILES]; mkdir [OUTPUT_DIRECTORY]; mv [OUTPUT_DIRECTORY]_* [OUTPUT_DIRECTORY]", "containerimage": {"image": "mcin/docker-fsl:latest", "index": "index.docker.io", "type": "docker"}, "inputs": [{"command-line-flag": "-n", "description": "Number of tissue-type classes; default = 3.", "value-key": "[NUM_CLASSES]", "type": "Number", "list": false, "minimum": 1, "integer": true, "optional": true, "id": "num_classes", "name": "Number of tissue-type classes"}, {"command-line-flag": "-I", "description": "Number of main-loop iterations during bias-field removal (default = 4).", "value-key": "[LOOP_ITERS]", "type": "Number", "list": false, "minimum": 1, "integer": true, "optional": true, "id": "loop_iters", "name": "Bias removal main-loop iterations"}, {"command-line-flag": "-l", "description": "Bias field smoothing extent (FWHM) in mm (default = 20).", "value-key": "[BF_SMOOTHING]", "optional": true, "list": false, "minimum": 0, "type": "Number", "id": "bf_smoothing", "name": "Bias field smoothing"}, {"command-line-flag": "-t", "description": "Type of image: 1 = T1, 2 = T2, 3 = PD. Default = T1.", "value-key": "[IMG_TYPE]", "type": "String", "list": false, "value-choices": ["1", "2", "3"], "optional": true, "id": "img_type", "name": "Image type"}, {"command-line-flag": "-f", "description": "Initial segmentation spatial smoothness (during bias field estimation); default = 0.02.", "value-key": "[INIT_SEG_SMOOTHNESS]", "type": "Number", "list": false, "optional": true, "id": "init_seg_smoothness", "name": "Initial segmentation smoothness"}, {"command-line-flag": "-g", "description": "Outputs a separate binary image for each tissue type", "value-key": "[BINARY_SEGMENTS]", "type": "Flag", "list": false, "optional": true, "id": "binary_segments", "name": "Binary images"}, {"command-line-flag": "-a", "description": "Initialize using priors. A FLIRT transform must be provided (e.g. std2input.mat)", "value-key": "[PRIOR_INIT]", "type": "File", "list": false, "optional": true, "id": "prior_init", "name": "Prior Initialization"}, {"command-line-flag": "--nopve", "description": "Turn off PVE (partial volume estimation).", "value-key": "[NO_PVE]", "optional": true, "list": false, "type": "Flag", "id": "no_pve", "name": "No PVE"}, {"command-line-flag": "-b", "description": "Output estimated bias field.", "value-key": "[BIAS_FIELD]", "type": "Flag", "list": false, "optional": true, "id": "bias_field", "name": "Bias field"}, {"command-line-flag": "-B", "description": "Output bias corrected image.", "value-key": "[BIAS_CORR_IMG]", "type": "Flag", "list": false, "optional": true, "id": "bias_corr_img", "name": "Bias corrected image"}, {"command-line-flag": "-N", "description": "Does not remove the bias field.", "value-key": "[NO_BIAS_RM]", "type": "Flag", "list": false, "optional": true, "id": "no_bias_rm", "name": "No bias removal"}, {"command-line-flag": "-o", "description": "The basename of the output files.", "default-value": "fast", "value-key": "[OUTPUT_BASENAME]", "type": "String", "list": false, "optional": false, "id": "output_basename", "name": "Output basename"}, {"command-line-flag": "-P", "description": "Use priors throughout the process", "value-key": "[PRIORS_THROUGHOUT]", "type": "Flag", "list": false, "requires-inputs": ["prior_init"], "optional": true, "id": "priors_throughout", "name": "Use priors throughout"}, {"command-line-flag": "-W", "description": "Number of segmentation-initialisation iterations; default = 15.", "value-key": "[SEG_INIT_ITERS]", "optional": true, "list": false, "minimum": 1, "integer": true, "type": "Number", "id": "seg_init_iters", "name": "Segmentation initialization iterations"}, {"command-line-flag": "-R", "description": "Spatial smoothness of mixeltype; default = 0.3.", "value-key": "[MIXEL_SMOOTHNESS]", "type": "Number", "list": false, "optional": true, "id": "mixel_smoothness", "name": "Mixeltype Smoothness"}, {"command-line-flag": "-O", "description": "Number of main-loop iterations after bias-field removal (default = 4).", "value-key": "[NUM_MAIN_LOOP_ITERS]", "optional": true, "list": false, "minimum": 1, "integer": true, "type": "Number", "id": "num_main_loop_iters", "name": "Main loop iterations"}, {"command-line-flag": "-H", "description": "Segmentation spatial smoothness; default = 0.1.", "value-key": "[HYPER_SEG_SMOOTHNESS]", "type": "Number", "list": false, "optional": true, "id": "hyper_seg_smoothness", "name": "Segmentation spatial smoothness"}, {"command-line-flag": "-v", "description": "Verbose mode", "value-key": "[VERBOSE]", "type": "Flag", "list": false, "optional": true, "id": "verbose", "name": "Verbose"}, {"command-line-flag": "-s", "description": "Filename containing the intensities", "value-key": "[MANUAL_INTENSITIES_FILE]", "type": "File", "list": false, "optional": true, "id": "manual_intensities_file", "name": "Manual segmentation"}, {"command-line-flag": "-p", "description": "Output individual probability maps", "value-key": "[OUTPUT_PROB_MAPS]", "optional": true, "list": false, "type": "Flag", "id": "output_prob_maps", "name": "Single probability maps"}, {"description": "Input file", "value-key": "[IN_FILES]", "type": "File", "list": false, "optional": false, "id": "in_files", "name": "Input file"}], "outputfiles": [{"description": "Output files from FSL FAST", "value-key": "[OUTPUT_DIRECTORY]", "id": "output_dir", "optional": false, "path-template": "[OUTPUT_BASENAME]", "name": "Output Directory"}], "tests": [{"name": "fsl_fast_test", "invocation": {"in_files": "sub-01_T1w.nii.gz", "output_basename": "img_fast"}, "assertions": {"exit-code": 0, "output-files": [{"id": "output_dir"}]}}], "ark_id": "https://n2t.net/ark:/70798/p74tqzhfx68d48dp0t", "platforms": [{"img": "/static/img/run_on_cbrain_green.png", "uri": "/cbrainredirect?cbrainurl=https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id%3D50"}]}, {"id": "zenodo.2639849", "title": "FNIRT", "description": "FNIRT, as implemented in Nipype (module: nipype.interfaces.fsl, interface: FNIRT).", "publicationdate": "2019-04-15", "deprecated": false, "downloads": 3818, "author": "Nipype (interface), Oxford Centre for Functional MRI of the Brain (FMRIB) (tool)", "version": "1.0.1", "doi": "10.5281/zenodo.2639849", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "fmri"], "source": "nipype-interface"}, "name": "FNIRT", "commandline": "fnirt [AFFINE_FILE] [APPLY_INMASK] [APPLY_INTENSITY_MAPPING] [APPLY_REFMASK] [BIAS_REGULARIZATION_LAMBDA] [BIASFIELD_RESOLUTION] [CONFIG_FILE] [DERIVE_FROM_REF] [FIELD_FILE] [FIELDCOEFF_FILE] [HESSIAN_PRECISION] [IN_FILE] [IN_FWHM] [IN_INTENSITYMAP_FILE] [INMASK_FILE] [INMASK_VAL] [INTENSITY_MAPPING_MODEL] [INTENSITY_MAPPING_ORDER] [INWARP_FILE] [JACOBIAN_FILE] [JACOBIAN_RANGE] [LOG_FILE] [MAX_NONLIN_ITER] [MODULATEDREF_FILE] [OUT_INTENSITYMAP_FILE] [REF_FILE] [REF_FWHM] [REFMASK_FILE] [REFMASK_VAL] [REGULARIZATION_LAMBDA] [REGULARIZATION_MODEL] [SKIP_IMPLICIT_IN_MASKING] [SKIP_IMPLICIT_REF_MASKING] [SKIP_INMASK] [SKIP_INTENSITY_MAPPING] [SKIP_LAMBDA_SSQ] [SKIP_REFMASK] [SPLINE_ORDER] [SUBSAMPLING_SCHEME] [WARP_RESOLUTION] [WARPED_FILE]", "url": "https://github.com/nipy/nipype/blob/master/nipype/interfaces/fsl/preprocess.py", "inputs": [{"id": "affine_file", "name": "Affine file", "type": "File", "value-key": "[AFFINE_FILE]", "command-line-flag": "--aff", "command-line-flag-separator": "=", "description": "An existing file name. Name of file containing affine transform.", "optional": true}, {"id": "apply_inmask", "name": "Apply inmask", "type": "Number", "list": true, "integer": true, "value-choices": [0, 1], "list-separator": ",", "value-key": "[APPLY_INMASK]", "command-line-flag": "--applyinmask", "command-line-flag-separator": "=", "description": "A list of items which are 0 or 1. List of iterations to use input mask on (1 to use, 0 to skip).", "optional": true}, {"id": "apply_intensity_mapping", "name": "Apply intensity mapping", "type": "Number", "list": true, "integer": true, "value-choices": [0, 1], "list-separator": ",", "value-key": "[APPLY_INTENSITY_MAPPING]", "command-line-flag": "--estint", "command-line-flag-separator": "=", "description": "A list of items which are 0 or 1. List of subsampling levels to apply intensity mapping for (0 to skip, 1 to apply).", "optional": true}, {"id": "apply_refmask", "name": "Apply refmask", "type": "Number", "list": true, "integer": true, "value-choices": [0, 1], "list-separator": ",", "value-key": "[APPLY_REFMASK]", "command-line-flag": "--applyrefmask", "command-line-flag-separator": "=", "description": "A list of items which are 0 or 1. List of iterations to use reference mask on (1 to use, 0 to skip).", "optional": true}, {"id": "bias_regularization_lambda", "name": "Bias regularization lambda", "type": "Number", "value-key": "[BIAS_REGULARIZATION_LAMBDA]", "command-line-flag": "--biaslambda", "command-line-flag-separator": "=", "description": "A float. Weight of regularisation for bias-field, default 10000.", "optional": true}, {"id": "biasfield_resolution", "name": "Biasfield resolution", "type": "Number", "list": true, "list-separator": ",", "min-list-entries": 3, "max-list-entries": 3, "integer": true, "value-key": "[BIASFIELD_RESOLUTION]", "command-line-flag": "--biasres", "command-line-flag-separator": "=", "description": "A tuple of the form: (an integer (int or long), an integer (int or long), an integer (int or long)). Resolution (in mm) of bias-field modelling local intensities, default 50, 50, 50.", "optional": true}, {"id": "config_file_choices", "name": "Config file", "type": "String", "value-key": "[CONFIG_FILE]", "command-line-flag": "--config", "command-line-flag-separator": "=", "description": "'t1_2_mni152_2mm' or 'fa_2_fmrib58_1mm' or an existing file name. Name of config file specifying command line arguments.", "optional": true, "value-choices": ["T1_2_MNI152_2mm", "FA_2_FMRIB58_1mm"]}, {"id": "config_file", "name": "Config file", "type": "File", "value-key": "[CONFIG_FILE]", "command-line-flag": "--config", "command-line-flag-separator": "=", "description": "'t1_2_mni152_2mm' or 'fa_2_fmrib58_1mm' or an existing file name. Name of config file specifying command line arguments.", "optional": true}, {"id": "derive_from_ref", "name": "Derive from ref", "type": "Number", "integer": true, "value-key": "[DERIVE_FROM_REF]", "command-line-flag": "--refderiv", "command-line-flag-separator": "=", "description": "A boolean. If true, ref image is used to calculate derivatives. default false.", "optional": true, "value-choices": [0, 1]}, {"id": "field_file", "name": "Field file", "type": "File", "value-key": "[FIELD_FILE]", "command-line-flag": "--fout", "command-line-flag-separator": "=", "description": "A file name. Name of output file with field.", "optional": true}, {"id": "fieldcoeff_file", "name": "Fieldcoeff file", "type": "File", "value-key": "[FIELDCOEFF_FILE]", "command-line-flag": "--cout", "command-line-flag-separator": "=", "description": "A file name. Name of output file with field coefficients.", "optional": true}, {"id": "hessian_precision", "name": "Hessian precision", "type": "String", "value-key": "[HESSIAN_PRECISION]", "command-line-flag": "--numprec", "command-line-flag-separator": "=", "description": "'double' or 'float'. Precision for representing hessian, double or float. default double.", "optional": true, "value-choices": ["double", "float"]}, {"id": "in_file", "name": "In file", "type": "File", "value-key": "[IN_FILE]", "command-line-flag": "--in", "command-line-flag-separator": "=", "description": "An existing file name. Name of input image.", "optional": false}, {"id": "in_fwhm", "name": "In fwhm", "type": "Number", "list": true, "integer": true, "list-separator": ",", "value-key": "[IN_FWHM]", "command-line-flag": "--infwhm", "command-line-flag-separator": "=", "description": "A list of items which are an integer (int or long). Fwhm (in mm) of gaussian smoothing kernel for input volume, default [6, 4, 2, 2].", "optional": true}, {"id": "in_intensitymap_file", "name": "In intensitymap file", "type": "File", "list": true, "min-list-entries": 1, "max-list-entries": 2, "value-key": "[IN_INTENSITYMAP_FILE]", "command-line-flag": "--intin", "command-line-flag-separator": "=", "description": "A list of from 1 to 2 items which are an existing file name. Name of file/files containing initial intensity mapping usually generated by previous fnirt run.", "optional": true}, {"id": "inmask_file", "name": "Inmask file", "type": "File", "value-key": "[INMASK_FILE]", "command-line-flag": "--inmask", "command-line-flag-separator": "=", "description": "An existing file name. Name of file with mask in input image space.", "optional": true}, {"id": "inmask_val", "name": "Inmask val", "type": "Number", "value-key": "[INMASK_VAL]", "command-line-flag": "--impinval", "command-line-flag-separator": "=", "description": "A float. Value to mask out in --in image. default =0.0.", "optional": true}, {"id": "intensity_mapping_model", "name": "Intensity mapping model", "type": "String", "value-key": "[INTENSITY_MAPPING_MODEL]", "command-line-flag": "--intmod", "command-line-flag-separator": "=", "description": "'none' or 'global_linear' or 'global_non_linear' or 'local_linear' or 'global_non_linear_with_bias' or 'local_non_linear'. Model for intensity-mapping.", "optional": true, "value-choices": ["none", "global_linear", "global_non_linear", "local_linear", "global_non_linear_with_bias", "local_non_linear"]}, {"id": "intensity_mapping_order", "name": "Intensity mapping order", "type": "Number", "integer": true, "value-key": "[INTENSITY_MAPPING_ORDER]", "command-line-flag": "--intorder", "command-line-flag-separator": "=", "description": "An integer (int or long). Order of poynomial for mapping intensities, default 5.", "optional": true}, {"id": "inwarp_file", "name": "Inwarp file", "type": "File", "value-key": "[INWARP_FILE]", "command-line-flag": "--inwarp", "command-line-flag-separator": "=", "description": "An existing file name. Name of file containing initial non-linear warps.", "optional": true}, {"id": "jacobian_file", "name": "Jacobian file", "type": "File", "value-key": "[JACOBIAN_FILE]", "command-line-flag": "--jout", "command-line-flag-separator": "=", "description": "A file name. Name of file for writing out the jacobian of the field (for diagnostic or vbm purposes).", "optional": true}, {"id": "jacobian_range", "name": "Jacobian range", "type": "Number", "list": true, "list-separator": ",", "min-list-entries": 2, "max-list-entries": 2, "value-key": "[JACOBIAN_RANGE]", "command-line-flag": "--jacrange", "command-line-flag-separator": "=", "description": "A tuple of the form: (a float, a float). Allowed range of jacobian determinants, default 0.01, 100.0.", "optional": true}, {"id": "log_file", "name": "Log file", "type": "File", "value-key": "[LOG_FILE]", "command-line-flag": "--logout", "command-line-flag-separator": "=", "description": "A file name. Name of log-file.", "optional": true}, {"id": "max_nonlin_iter", "name": "Max nonlin iter", "type": "Number", "list": true, "integer": true, "list-separator": ",", "value-key": "[MAX_NONLIN_ITER]", "command-line-flag": "--miter", "command-line-flag-separator": "=", "description": "A list of items which are an integer (int or long). Max # of non-linear iterations list, default [5, 5, 5, 5].", "optional": true}, {"id": "modulatedref_file", "name": "Modulatedref file", "type": "File", "value-key": "[MODULATEDREF_FILE]", "command-line-flag": "--refout", "command-line-flag-separator": "=", "description": "A file name. Name of file for writing out intensity modulated --ref (for diagnostic purposes).", "optional": true}, {"id": "out_intensitymap_file", "name": "Out intensitymap file", "type": "File", "value-key": "[OUT_INTENSITYMAP_FILE]", "command-line-flag": "--intout", "command-line-flag-separator": "=", "description": "A file name. Name of files for writing information pertaining to intensity mapping.", "optional": true}, {"id": "ref_file", "name": "Ref file", "type": "File", "value-key": "[REF_FILE]", "command-line-flag": "--ref", "command-line-flag-separator": "=", "description": "An existing file name. Name of reference image.", "optional": false}, {"id": "ref_fwhm", "name": "Ref fwhm", "type": "Number", "list": true, "integer": true, "list-separator": ",", "value-key": "[REF_FWHM]", "command-line-flag": "--reffwhm", "command-line-flag-separator": "=", "description": "A list of items which are an integer (int or long). Fwhm (in mm) of gaussian smoothing kernel for ref volume, default [4, 2, 0, 0].", "optional": true}, {"id": "refmask_file", "name": "Refmask file", "type": "File", "value-key": "[REFMASK_FILE]", "command-line-flag": "--refmask", "command-line-flag-separator": "=", "description": "An existing file name. Name of file with mask in reference space.", "optional": true}, {"id": "refmask_val", "name": "Refmask val", "type": "Number", "value-key": "[REFMASK_VAL]", "command-line-flag": "--imprefval", "command-line-flag-separator": "=", "description": "A float. Value to mask out in --ref image. default =0.0.", "optional": true}, {"id": "regularization_lambda", "name": "Regularization lambda", "type": "Number", "list": true, "list-separator": ",", "value-key": "[REGULARIZATION_LAMBDA]", "command-line-flag": "--lambda", "command-line-flag-separator": "=", "description": "A list of items which are a float. Weight of regularisation, default depending on --ssqlambda and --regmod switches. see user documetation.", "optional": true}, {"id": "regularization_model", "name": "Regularization model", "type": "String", "value-key": "[REGULARIZATION_MODEL]", "command-line-flag": "--regmod", "command-line-flag-separator": "=", "description": "'membrane_energy' or 'bending_energy'. Model for regularisation of warp-field [membrane_energy bending_energy], default bending_energy.", "optional": true, "value-choices": ["membrane_energy", "bending_energy"]}, {"id": "skip_implicit_in_masking", "name": "Skip implicit in masking", "type": "Flag", "value-key": "[SKIP_IMPLICIT_IN_MASKING]", "command-line-flag": "--impinm=0", "description": "A boolean. Skip implicit masking  based on value in --in image. default = 0.", "optional": true}, {"id": "skip_implicit_ref_masking", "name": "Skip implicit ref masking", "type": "Flag", "value-key": "[SKIP_IMPLICIT_REF_MASKING]", "command-line-flag": "--imprefm=0", "description": "A boolean. Skip implicit masking  based on value in --ref image. default = 0.", "optional": true}, {"id": "skip_inmask", "name": "Skip inmask", "type": "Flag", "value-key": "[SKIP_INMASK]", "command-line-flag": "--applyinmask=0", "description": "A boolean. Skip specified inmask if set, default false.", "optional": true}, {"id": "skip_intensity_mapping", "name": "Skip intensity mapping", "type": "Flag", "value-key": "[SKIP_INTENSITY_MAPPING]", "command-line-flag": "--estint=0", "description": "A boolean. Skip estimate intensity-mapping default false.", "optional": true}, {"id": "skip_lambda_ssq", "name": "Skip lambda ssq", "type": "Flag", "value-key": "[SKIP_LAMBDA_SSQ]", "command-line-flag": "--ssqlambda=0", "description": "A boolean. If true, lambda is not weighted by current ssq, default false.", "optional": true}, {"id": "skip_refmask", "name": "Skip refmask", "type": "Flag", "value-key": "[SKIP_REFMASK]", "command-line-flag": "--applyrefmask=0", "description": "A boolean. Skip specified refmask if set, default false.", "optional": true}, {"id": "spline_order", "name": "Spline order", "type": "Number", "integer": true, "value-key": "[SPLINE_ORDER]", "command-line-flag": "--splineorder", "command-line-flag-separator": "=", "description": "An integer (int or long). Order of spline, 2->quadratic spline, 3->cubic spline. default=3.", "optional": true, "value-choices": [2, 3]}, {"id": "subsampling_scheme", "name": "Subsampling scheme", "type": "Number", "list": true, "integer": true, "list-separator": ",", "value-key": "[SUBSAMPLING_SCHEME]", "command-line-flag": "--subsamp", "command-line-flag-separator": "=", "description": "A list of items which are an integer (int or long). Sub-sampling scheme, list, default [4, 2, 1, 1].", "optional": true}, {"id": "warp_resolution", "name": "Warp resolution", "type": "Number", "list": true, "list-separator": ",", "min-list-entries": 3, "max-list-entries": 3, "integer": true, "value-key": "[WARP_RESOLUTION]", "command-line-flag": "--warpres", "command-line-flag-separator": "=", "description": "A tuple of the form: (an integer (int or long), an integer (int or long), an integer (int or long)). (approximate) resolution (in mm) of warp basis in x-, y- and z-direction, default 10, 10, 10.", "optional": true}, {"id": "warped_file", "name": "Warped file", "type": "File", "value-key": "[WARPED_FILE]", "command-line-flag": "--iout", "command-line-flag-separator": "=", "description": "A file name. Name of output image.", "optional": true}], "outputfiles": [{"name": "Field file", "id": "field_file_outfile", "path-template": "[FIELD_FILE]", "optional": true, "description": "A file name. File with warp field."}, {"name": "Fieldcoeff file", "id": "fieldcoeff_file_outfile", "path-template": "[FIELDCOEFF_FILE]", "optional": true, "description": "An existing file name. File with field coefficients."}, {"name": "Jacobian file", "id": "jacobian_file_outfile", "path-template": "[JACOBIAN_FILE]", "optional": true, "description": "A file name. File containing jacobian of the field."}, {"name": "Log file", "id": "log_file_outfile", "path-template": "[LOG_FILE]", "optional": true, "description": "A file name. Name of log-file."}, {"name": "Modulatedref file", "id": "modulatedref_file_outfile", "path-template": "[MODULATEDREF_FILE]", "optional": true, "description": "A file name. File containing intensity modulated --ref."}, {"name": "Out intensitymap file", "id": "out_intensitymap_file_outfile", "path-template": "[OUT_INTENSITYMAP_FILE]", "optional": true, "description": "A list of from 2 to 2 items which are a file name. Files containing info pertaining to intensity mapping.", "list": true}, {"name": "Warped file", "id": "warped_file_outfile", "path-template": "[WARPED_FILE]", "optional": true, "description": "An existing file name. Warped image."}], "groups": [{"id": "config_file_group", "name": "Config file group", "members": ["config_file", "config_file_choices"], "mutually-exclusive": true}, {"id": "mutex_group", "name": "Mutex group", "members": ["apply_refmask", "skip_refmask"], "mutually-exclusive": true}, {"id": "mutex_group_2", "name": "Mutex group 2", "members": ["apply_inmask", "skip_inmask"], "mutually-exclusive": true}, {"id": "mutex_group_3", "name": "Mutex group 3", "members": ["skip_intensity_mapping", "apply_intensity_mapping"], "mutually-exclusive": true}], "toolversion": "1.0.1", "containerimage": {"image": "mcin/docker-fsl:latest", "type": "docker", "index": "index.docker.io"}, "ark_id": "https://n2t.net/ark:/70798/p7jhjwdw53jdw2r5q3", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.1451003", "title": "qeeg", "description": "qeeg application", "publicationdate": "2018-10-08", "deprecated": false, "downloads": 3136, "author": "Neuroinformatics Collaboratory", "version": "undefined", "doi": "10.5281/zenodo.1451003", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "eeg"]}, "toolversion": "undefined", "name": "qeeg", "descriptorurl": "https://github.com/big-data-lab-team/cbrain-plugins-eeg/blob/master/cbrain_task_descriptors/qeeg.json", "commandline": "qeegt.sh --input [input_directory]/[basename] --state [state] --lwin [lwin] --fmin [fmin] --freqres [freqres] --fmax [fmax] --wbands [wbands] [brain] [pg_apply] [bbsm] [nbsm] [spectra] [bbsmz] [nbsmz] [ssz] [corr] [cohe] [phdiff] [fcorr] [storexyz] --output \"results\" ", "inputs": [{"description": "Directory containing the files to process.", "value-key": "[input_directory]", "optional": false, "list": false, "type": "File", "id": "input_directory", "name": "Input directory"}, {"description": "Basename of the file to process in the input directory.", "value-key": "[basename]", "optional": false, "list": false, "type": "String", "id": "basename", "name": "Basename"}, {"description": "Example: \"A\". EEG state to be analyzed. The program will look for existing analysis windows labelled as state 'A' (Eyes Closed).", "default-value": "A", "value-key": "[state]", "optional": false, "list": false, "type": "String", "id": "state", "name": "State"}, {"description": "Length of the analysis window in seconds.", "default-value": 2.56, "value-key": "[lwin]", "optional": false, "list": false, "minimum": 0, "type": "Number", "id": "lwin", "name": "Window length"}, {"description": "Low cut frequency for analysis. Example: \"0.390625\".", "default-value": 0.390625, "value-key": "[fmin]", "optional": false, "list": false, "minimum": 0, "type": "Number", "id": "fmin", "name": "fmin"}, {"description": "Fequency resolution for analysis. Example: \"0.390625\". The analysis will use a frequency band like this: fmin:freqres:fmax. The program will compare this interval with the interval that is obtained for the real frequency parameters of the signal and will match both of them.", "default-value": 0.390625, "value-key": "[freqres]", "optional": false, "list": false, "type": "Number", "id": "freqres", "name": "freqres"}, {"description": "High cut frequency for analysis. Example: \"19.11\".", "default-value": 19.11, "value-key": "[fmax]", "optional": false, "list": false, "type": "Number", "id": "fmax", "name": "fmax"}, {"description": "Broad Bands definition. A string representing a 5x2 matrix of real numbers, where rows are separated by ';' and columns by spaces. Example: \"1.56 3.51; 3.9 7.41; 7.8 12.48; 12.87 19.11; 1.56 19.11\".", "default-value": "1.56 3.51; 3.9 7.41; 7.8 12.48; 12.87 19.11; 1.56 19.11", "value-key": "[wbands]", "optional": false, "list": false, "type": "String", "id": "wbands", "name": "wbands"}, {"command-line-flag": "--brain", "description": "Restricts the inverse solution to only gray matter. Otherwise, deep structure (basal ganglia) will be included in the grid.", "default-value": true, "value-key": "[brain]", "optional": true, "type": "Flag", "id": "brain", "name": "Brain"}, {"command-line-flag": "--pg_apply", "description": "Substracts the Global Scale Factor (Geometric Power) from the EEG signal.", "default-value": true, "value-key": "[pg_apply]", "optional": true, "type": "Flag", "id": "pg_apply", "name": "PG Apply"}, {"command-line-flag": "--bbsm", "description": "Calculates the Broad Band Spectral Model.", "default-value": true, "value-key": "[bbsm]", "optional": true, "type": "Flag", "id": "bbsm", "name": "Broad Band Spectral Model"}, {"command-line-flag": "--nbsm", "description": "Calculates the Narrow Band Spectral Model.", "default-value": true, "value-key": "[nbsm]", "optional": true, "type": "Flag", "id": "nbsm", "name": "Narrow Band Spectral Model"}, {"command-line-flag": "--spectra", "description": "Calculates the Spectra at the EEG sources.", "default-value": true, "value-key": "[spectra]", "optional": true, "type": "Flag", "id": "spectra", "name": "Spectra"}, {"command-line-flag": "--bbsmz", "description": "Calculates the Broad Band Spectral Model Z values.", "default-value": true, "value-key": "[bbsmz]", "optional": true, "type": "Flag", "id": "bbsmz", "name": "Broad Band Spectral Model Z values"}, {"command-line-flag": "--nbsmz", "description": "Calculates the Narrow Band Spectral Model Z values.", "default-value": true, "value-key": "[nbsmz]", "optional": true, "type": "Flag", "id": "nbsmz", "name": "Narrow Band Spectral Model Z values"}, {"command-line-flag": "--ssz", "description": "Calculates the Sources Spectra Z values.", "default-value": true, "value-key": "[ssz]", "optional": true, "type": "Flag", "id": "ssz", "name": "Source Spectra Z"}, {"command-line-flag": "--corr", "description": "Calculates the correlations matrix bewteen all pairs of channels for each epoch.", "default-value": true, "value-key": "[corr]", "optional": true, "type": "Flag", "id": "corr", "name": "Correlations matrix"}, {"command-line-flag": "--cohe", "description": "Calculates the coherence matrix bewteen all pairs of channels for each frequency.", "default-value": true, "value-key": "[cohe]", "optional": true, "type": "Flag", "id": "cohe", "name": "Coherence matrix"}, {"command-line-flag": "--phdiff", "description": "Calculates the phase difference matrix bewteen all pairs of channels for each frequency.", "default-value": true, "value-key": "[phdiff]", "optional": true, "type": "Flag", "id": "phdiff", "name": "Phase difference matrix"}, {"command-line-flag": "--fcorr", "description": "Calculates  the frequency domain correlations bewteen all pairs of channels for each frequency and each epoch.", "default-value": true, "value-key": "[fcorr]", "optional": true, "type": "Flag", "id": "fcorr", "name": "Frequency domain correlations"}, {"command-line-flag": "--storexyz", "description": "Stores the XYZ components of the solutions at the sources.", "default-value": true, "value-key": "[storexyz]", "optional": true, "type": "Flag", "id": "storexyz", "name": "XYZ components"}], "containerimage": {"image": "mcin/qeeg:latest", "type": "docker"}, "outputfiles": [{"description": "A folder containing the output files.", "list": false, "id": "folder_out", "optional": false, "path-template": "results", "name": "Output folder"}], "ark_id": "https://n2t.net/ark:/70798/p7p3d8tqm9zzg89rh6", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.1895219", "title": "BIDS App - fmriprep", "description": "fMRIprep is a functional magneticresonance image pre-processing pipeline that is designed to provide an easily accessible, state-of-the-art interface that is robust to differences in scan acquisition protocols and that requires minimal user input, while providing easily interpretable and comprehensive error and output reporting. https://fmriprep.readthedocs.io", "publicationdate": "2018-12-03", "deprecated": false, "downloads": 3121, "author": "Poldrack lab", "version": "1.2.3", "doi": "10.5281/zenodo.1895219", "schemaversion": "0.5", "container": "docker", "tags": {"application-type": ["bids"], "domain": ["neuroinformatics", "fmri"]}, "commandline": "fmriprep [BIDS_DIR] [OUTPUT_DIR] [ANALYSIS_LEVEL] [VERSION] [PARTICIPANT_LABEL] [TASK_ID] [NTHREADS] [OMP_NTHREADS] [MEM_MB] [LOW_MEM] [USE_PLUGIN] [ANAT_ONLY] [BOILERPLATE] [IGNORE_AROMA_DENOISING_ERRORS] [VERBOSE_COUNT] [DEBUG] [IGNORE] [LONGITUDINAL] [T2S_COREG] [BOLD2T1W_DOF] [OUTPUT_SPACE] [USE_BBR] [TEMPLATE] [OUTPUT_GRID_REFERENCE] [TEMPLATE_RESAMPLING_GRID] [MEDIAL_SURFACE_NAN] [USE_AROMA] [AROMA_MELODIC_DIMENSIONALITY] [SKULL_STRIP_TEMPLATE] [SKULL_STRIP_FIXED_SEED] [FMAP_BSPLINE] [FMAP_NO_DEMEAN] [USE_SYN_SDC] [FORCE_SYN] [FS_LICENSE_FILE] [HIRES] [CIFTI_OUTPUT] [RUN_RECONALL] [WORK_DIR] [RESOURCE_MONITOR] [REPORTS_ONLY] [RUN_UUID] [WRITE_GRAPH] [STOP_ON_FIRST_CRASH] [NOTRACK] [SLOPPY]", "url": "https://fmriprep.readthedocs.io", "inputs": [{"description": "the root folder of a BIDS valid dataset (sub-XXXXX folders should be found at the top level in this folder).", "id": "bids_dir", "name": "bids_dir", "optional": false, "type": "String", "value-key": "[BIDS_DIR]"}, {"description": "the output path for the outcomes of preprocessing and visual reports", "id": "output_dir", "name": "output_dir", "optional": false, "type": "String", "value-key": "[OUTPUT_DIR]"}, {"description": "processing stage to be run, only \"participant\" in the case of FMRIPREP (see BIDS-Apps specification).", "id": "analysis_level", "name": "analysis_level", "optional": false, "type": "String", "value-choices": ["participant"], "value-key": "[ANALYSIS_LEVEL]"}, {"command-line-flag": "--version", "default-value": "==SUPPRESS==", "description": "show program's version number and exit", "id": "version", "name": "version", "optional": true, "type": "String", "value-key": "[VERSION]"}, {"command-line-flag": "--participant_label", "description": "a space delimited list of participant identifiers or a single identifier (the sub- prefix can be removed)", "id": "participant_label", "list": true, "name": "participant_label", "optional": true, "type": "String", "value-key": "[PARTICIPANT_LABEL]"}, {"command-line-flag": "-t", "description": "select a specific task to be processed", "id": "task_id", "name": "task_id", "optional": true, "type": "String", "value-key": "[TASK_ID]"}, {"command-line-flag": "--nthreads", "description": "maximum number of threads across all processes", "id": "nthreads", "name": "nthreads", "optional": true, "type": "Number", "value-key": "[NTHREADS]"}, {"command-line-flag": "--omp-nthreads", "description": "maximum number of threads per-process", "id": "omp_nthreads", "name": "omp_nthreads", "optional": true, "type": "Number", "value-key": "[OMP_NTHREADS]"}, {"command-line-flag": "--mem_mb", "description": "upper bound memory limit for FMRIPREP processes", "id": "mem_mb", "name": "mem_mb", "optional": true, "type": "Number", "value-key": "[MEM_MB]"}, {"command-line-flag": "--low-mem", "description": "attempt to reduce memory usage (will increase disk usage in working directory)", "id": "low_mem", "name": "low_mem", "optional": true, "type": "Flag", "value-key": "[LOW_MEM]"}, {"command-line-flag": "--use-plugin", "description": "nipype plugin configuration file", "id": "use_plugin", "name": "use_plugin", "optional": true, "type": "String", "value-key": "[USE_PLUGIN]"}, {"command-line-flag": "--anat-only", "description": "run anatomical workflows only", "id": "anat_only", "name": "anat_only", "optional": true, "type": "Flag", "value-key": "[ANAT_ONLY]"}, {"command-line-flag": "--boilerplate", "description": "generate boilerplate only", "id": "boilerplate", "name": "boilerplate", "optional": true, "type": "Flag", "value-key": "[BOILERPLATE]"}, {"command-line-flag": "--ignore-aroma-denoising-errors", "description": "ignores the errors ICA_AROMA returns when there are no components classified as either noise or signal", "id": "ignore_aroma_denoising_errors", "name": "ignore_aroma_denoising_errors", "optional": true, "type": "Flag", "value-key": "[IGNORE_AROMA_DENOISING_ERRORS]"}, {"command-line-flag": "-v", "description": "increases log verbosity for each occurence, debug level is -vvv", "id": "verbose_count", "name": "verbose_count", "optional": true, "type": "String", "value-key": "[VERBOSE_COUNT]"}, {"command-line-flag": "--debug", "description": "DEPRECATED - Does not do what you want.", "id": "debug", "name": "debug", "optional": true, "type": "Flag", "value-key": "[DEBUG]"}, {"command-line-flag": "--ignore", "description": "ignore selected aspects of the input dataset to disable corresponding parts of the workflow (a space delimited list)", "id": "ignore", "list": true, "name": "ignore", "optional": true, "type": "String", "value-choices": ["fieldmaps", "slicetiming", "sbref"], "value-key": "[IGNORE]"}, {"command-line-flag": "--longitudinal", "description": "treat dataset as longitudinal - may increase runtime", "id": "longitudinal", "name": "longitudinal", "optional": true, "type": "Flag", "value-key": "[LONGITUDINAL]"}, {"command-line-flag": "--t2s-coreg", "description": "If provided with multi-echo BOLD dataset, create T2*-map and perform T2*-driven coregistration. When multi-echo data is provided and this option is not enabled, standard EPI-T1 coregistration is performed using the middle echo.", "id": "t2s_coreg", "name": "t2s_coreg", "optional": true, "type": "Flag", "value-key": "[T2S_COREG]"}, {"command-line-flag": "--bold2t1w-dof", "default-value": 6, "description": "Degrees of freedom when registering BOLD to T1w images. 6 degrees (rotation and translation) are used by default.", "id": "bold2t1w_dof", "name": "bold2t1w_dof", "optional": true, "type": "Number", "value-choices": [6, 9, 12], "value-key": "[BOLD2T1W_DOF]"}, {"command-line-flag": "--output-space", "default-value": ["template", "fsaverage5"], "description": "volume and surface spaces to resample functional series into\n - T1w: subject anatomical volume\n - template: normalization target specified by --template\n - fsnative: individual subject surface\n - fsaverage*: FreeSurfer average meshes\nthis argument can be single value or a space delimited list,\nfor example: --output-space T1w fsnative", "id": "output_space", "list": true, "name": "output_space", "optional": true, "type": "String", "value-choices": ["T1w", "template", "fsnative", "fsaverage", "fsaverage6", "fsaverage5"], "value-key": "[OUTPUT_SPACE]"}, {"command-line-flag": "--force-bbr", "description": "Always use boundary-based registration (no goodness-of-fit checks)", "id": "use_bbr", "name": "use_bbr", "optional": true, "type": "Flag", "value-key": "[USE_BBR]"}, {"command-line-flag": "--template", "default-value": "MNI152NLin2009cAsym", "description": "volume template space (default: MNI152NLin2009cAsym)", "id": "template", "name": "template", "optional": true, "type": "String", "value-choices": ["MNI152NLin2009cAsym"], "value-key": "[TEMPLATE]"}, {"command-line-flag": "--output-grid-reference", "description": "Deprecated after FMRIPREP 1.0.8. Please use --template-resampling-grid instead.", "id": "output_grid_reference", "name": "output_grid_reference", "optional": true, "type": "String", "value-key": "[OUTPUT_GRID_REFERENCE]"}, {"command-line-flag": "--template-resampling-grid", "default-value": "native", "description": "Keyword (\"native\", \"1mm\", or \"2mm\") or path to an existing file. Allows to define a reference grid for the resampling of BOLD images in template space. Keyword \"native\" will use the original BOLD grid as reference. Keywords \"1mm\" and \"2mm\" will use the corresponding isotropic template resolutions. If a path is given, the grid of that image will be used. It determines the field of view and resolution of the output images, but is not used in normalization.", "id": "template_resampling_grid", "name": "template_resampling_grid", "optional": true, "type": "String", "value-key": "[TEMPLATE_RESAMPLING_GRID]"}, {"command-line-flag": "--medial-surface-nan", "description": "Replace medial wall values with NaNs on functional GIFTI files. Only performed for GIFTI files mapped to a freesurfer subject (fsaverage or fsnative).", "id": "medial_surface_nan", "name": "medial_surface_nan", "optional": true, "type": "Flag", "value-key": "[MEDIAL_SURFACE_NAN]"}, {"command-line-flag": "--use-aroma", "description": "add ICA_AROMA to your preprocessing stream", "id": "use_aroma", "name": "use_aroma", "optional": true, "type": "Flag", "value-key": "[USE_AROMA]"}, {"command-line-flag": "--aroma-melodic-dimensionality", "default-value": -200, "description": "Exact or maximum number of MELODIC components to estimate (positive = exact, negative = maximum)", "id": "aroma_melodic_dimensionality", "name": "aroma_melodic_dimensionality", "optional": true, "type": "Number", "value-key": "[AROMA_MELODIC_DIMENSIONALITY]"}, {"command-line-flag": "--skull-strip-template", "default-value": "OASIS", "description": "select ANTs skull-stripping template (default: OASIS))", "id": "skull_strip_template", "name": "skull_strip_template", "optional": true, "type": "String", "value-choices": ["OASIS", "NKI"], "value-key": "[SKULL_STRIP_TEMPLATE]"}, {"command-line-flag": "--skull-strip-fixed-seed", "description": "do not use a random seed for skull-stripping - will ensure run-to-run replicability when used with --omp-nthreads 1", "id": "skull_strip_fixed_seed", "name": "skull_strip_fixed_seed", "optional": true, "type": "Flag", "value-key": "[SKULL_STRIP_FIXED_SEED]"}, {"command-line-flag": "--fmap-bspline", "description": "fit a B-Spline field using least-squares (experimental)", "id": "fmap_bspline", "name": "fmap_bspline", "optional": true, "type": "Flag", "value-key": "[FMAP_BSPLINE]"}, {"command-line-flag": "--fmap-no-demean", "default-value": true, "description": "do not remove median (within mask) from fieldmap", "id": "fmap_no_demean", "name": "fmap_no_demean", "optional": true, "type": "String", "value-key": "[FMAP_NO_DEMEAN]"}, {"command-line-flag": "--use-syn-sdc", "description": "EXPERIMENTAL: Use fieldmap-free distortion correction", "id": "use_syn_sdc", "name": "use_syn_sdc", "optional": true, "type": "Flag", "value-key": "[USE_SYN_SDC]"}, {"command-line-flag": "--force-syn", "description": "EXPERIMENTAL/TEMPORARY: Use SyN correction in addition to fieldmap correction, if available", "id": "force_syn", "name": "force_syn", "optional": true, "type": "Flag", "value-key": "[FORCE_SYN]"}, {"command-line-flag": "--fs-license-file", "description": "Path to FreeSurfer license key file. Get it (for free) by registering at https://surfer.nmr.mgh.harvard.edu/registration.html", "id": "fs_license_file", "name": "fs_license_file", "optional": true, "uses-absolute-path": true, "type": "File", "value-key": "[FS_LICENSE_FILE]"}, {"command-line-flag": "--no-submm-recon", "default-value": true, "description": "disable sub-millimeter (hires) reconstruction", "id": "hires", "name": "hires", "optional": true, "type": "String", "value-key": "[HIRES]"}, {"command-line-flag": "--cifti-output", "description": "output BOLD files as CIFTI dtseries", "id": "cifti_output", "name": "cifti_output", "optional": true, "type": "Flag", "value-key": "[CIFTI_OUTPUT]"}, {"command-line-flag": "--fs-no-reconall", "default-value": true, "description": "disable FreeSurfer surface preprocessing. Note : `--no-freesurfer` is deprecated and will be removed in 1.2. Use `--fs-no-reconall` instead.", "id": "run_reconall", "name": "run_reconall", "optional": true, "type": "String", "value-key": "[RUN_RECONALL]"}, {"command-line-flag": "-w", "description": "path where intermediate results should be stored", "id": "work_dir", "name": "work_dir", "optional": true, "type": "String", "value-key": "[WORK_DIR]"}, {"command-line-flag": "--resource-monitor", "description": "enable Nipype's resource monitoring to keep track of memory and CPU usage", "id": "resource_monitor", "name": "resource_monitor", "optional": true, "type": "Flag", "value-key": "[RESOURCE_MONITOR]"}, {"command-line-flag": "--reports-only", "description": "only generate reports, don't run workflows. This will only rerun report aggregation, not reportlet generation for specific nodes.", "id": "reports_only", "name": "reports_only", "optional": true, "type": "Flag", "value-key": "[REPORTS_ONLY]"}, {"command-line-flag": "--run-uuid", "description": "Specify UUID of previous run, to include error logs in report. No effect without --reports-only.", "id": "run_uuid", "name": "run_uuid", "optional": true, "type": "String", "value-key": "[RUN_UUID]"}, {"command-line-flag": "--write-graph", "description": "Write workflow graph.", "id": "write_graph", "name": "write_graph", "optional": true, "type": "Flag", "value-key": "[WRITE_GRAPH]"}, {"command-line-flag": "--stop-on-first-crash", "description": "Force stopping on first crash, even if a work directory was specified.", "id": "stop_on_first_crash", "name": "stop_on_first_crash", "optional": true, "type": "Flag", "value-key": "[STOP_ON_FIRST_CRASH]"}, {"command-line-flag": "--notrack", "description": "Opt-out of sending tracking information of this run to the FMRIPREP developers. This information helps to improve FMRIPREP and provides an indicator of real world usage crucial for obtaining funding.", "id": "notrack", "name": "notrack", "optional": true, "type": "Flag", "value-key": "[NOTRACK]"}, {"command-line-flag": "--sloppy", "description": "Use low-quality tools for speed - TESTING ONLY", "id": "sloppy", "name": "sloppy", "optional": true, "type": "Flag", "value-key": "[SLOPPY]"}], "name": "BIDS App - fmriprep", "containerimage": {"type": "docker", "image": "poldracklab/fmriprep:1.2.3"}, "toolversion": "1.2.3", "ark_id": "https://n2t.net/ark:/70798/p7xnrc72x976b4qc91", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.1484547", "title": "BIDS App - FreeSurfer 6.0", "description": "BIDS App version of freesurfer 6.0, from https://github.com/BIDS-Apps/freesurfer, see the readme there for more details, note it needs a license file to run", "publicationdate": "2018-11-12", "deprecated": false, "downloads": 3114, "author": "Shawn T. Brown, McGill University <stbrown@mcin.ca>", "version": "v6.0.0", "doi": "10.5281/zenodo.1484547", "schemaversion": "0.5", "container": "singularity", "tags": {}, "commandline": "mkdir -p [OUTPUT_DIR] ; /run.py [BIDS_DIR] [OUTPUT_DIR] [ANALYSIS_LEVEL] [PARTICIPANT_LABEL] [SESSION_LABEL] [N_CPUS] [STAGES] [STEPS] [TEMPLATE_NAME] [LICENSE_FILE] [ACQUISITION_LABEL] [REFINE_PIAL_ACQUISITION_LABEL] [MULTIPLE_SESSIONS] [REFINE_PIAL] [HIRES_MODE] [PARCELLATIONS] [MEASUREMENTS] [VERSION] [BIDS_VALIDATOR_CONFIG] [SKIP_BIDS_VALIDATOR] [3T]", "containerimage": {"image": "shots47s/bids-freesurfer-6.0", "type": "singularity"}, "groups": [{"description": "For a participants analysis, an output directory name must be specified. For a group analysis, a directory containing the output of participant-level analyses must be selected. ", "id": "output_directory", "members": ["output_dir", "participant_level_analysis_dir"], "mutually-exclusive": true, "name": "Output Directory", "one-is-required": true}], "inputs": [{"description": "The directory with the input dataset formatted according to the BIDS standard.", "id": "bids_dir", "name": "bids_dir", "optional": false, "type": "String", "value-key": "[BIDS_DIR]"}, {"description": "The directory where the output files should be stored. If you are running group level analysis this folder should be prepopulated with the results of theparticipant level analysis.", "id": "output_dir", "name": "output_dir", "optional": true, "type": "String", "value-key": "[OUTPUT_DIR]"}, {"description": "Level of the analysis that will be performed. Multiple participant level analyses can be run independently (in parallel) using the same output_dir. \"group1\" creates study specific group template. \"group2\" exports group stats tables for cortical parcellation, subcortical segmentation a table with euler numbers.", "id": "analysis_level", "name": "analysis_level", "optional": false, "type": "String", "value-choices": ["participant", "group1", "group2"], "value-key": "[ANALYSIS_LEVEL]"}, {"command-line-flag": "--participant_label", "description": "The label of the participant that should be analyzed. The label corresponds to sub-<participant_label> from the BIDS spec (so it does not include \"sub-\"). If this parameter is not provided all subjects should be analyzed. Multiple participants can be specified with a space separated list.", "id": "participant_label", "list": true, "name": "participant_label", "optional": true, "type": "String", "value-key": "[PARTICIPANT_LABEL]"}, {"command-line-flag": "--session_label", "description": "The label of the session that should be analyzed. The label corresponds to ses-<session_label> from the BIDS spec (so it does not include \"ses-\"). If this parameter is not provided all sessions should be analyzed. Multiple sessions can be specified with a space separated list.", "id": "session_label", "list": true, "name": "session_label", "optional": true, "type": "String", "value-key": "[SESSION_LABEL]"}, {"command-line-flag": "--n_cpus", "default-value": 1, "description": "Number of CPUs/cores available to use.", "id": "n_cpus", "name": "n_cpus", "optional": true, "type": "Number", "value-key": "[N_CPUS]"}, {"command-line-flag": "--stages", "default-value": ["autorecon-all"], "description": "Autorecon stages to run.", "id": "stages", "list": true, "name": "stages", "optional": true, "type": "String", "value-choices": ["autorecon1", "autorecon2", "autorecon2-cp", "autorecon2-wm", "autorecon-pial", "autorecon3", "autorecon-all", "all"], "value-key": "[STAGES]"}, {"command-line-flag": "--steps", "default-value": ["cross-sectional", "template", "longitudinal"], "description": "Longitudinal pipeline steps to run.", "id": "steps", "list": true, "name": "steps", "optional": true, "type": "String", "value-choices": ["cross-sectional", "template", "longitudinal"], "value-key": "[STEPS]"}, {"command-line-flag": "--template_name", "default-value": "average", "description": "Name for the custom group level template generated for this dataset", "id": "template_name", "name": "template_name", "optional": true, "type": "String", "value-key": "[TEMPLATE_NAME]"}, {"command-line-flag": "--license_file", "description": "Path to FreeSurfer license key file. To obtain it you need to register (for free) at https://surfer.nmr.mgh.harvard.edu/registration.html", "id": "license_file", "name": "license_file", "optional": false, "type": "String", "value-key": "[LICENSE_FILE]"}, {"command-line-flag": "--acquisition_label", "description": "If the dataset contains multiple T1 weighted images from different acquisitions which one should be used? Corresponds to \"acq-<acquisition_label>\"", "id": "acquisition_label", "name": "acquisition_label", "optional": true, "type": "String", "value-key": "[ACQUISITION_LABEL]"}, {"command-line-flag": "--refine_pial_acquisition_label", "description": "If the dataset contains multiple T2 or FLAIR weighted images from different acquisitions which one should be used? Corresponds to \"acq-<acquisition_label>\"", "id": "refine_pial_acquisition_label", "name": "refine_pial_acquisition_label", "optional": true, "type": "String", "value-key": "[REFINE_PIAL_ACQUISITION_LABEL]"}, {"command-line-flag": "--multiple_sessions", "default-value": "longitudinal", "description": "For datasets with multiday sessions where you do not want to use the longitudinal pipeline, i.e., sessions were back-to-back, set this to multiday, otherwise sessions with T1w data will be considered independent sessions for longitudinal analysis.", "id": "multiple_sessions", "name": "multiple_sessions", "optional": true, "type": "String", "value-choices": ["longitudinal", "multiday"], "value-key": "[MULTIPLE_SESSIONS]"}, {"command-line-flag": "--refine_pial", "default-value": ["T2"], "description": "If the dataset contains 3D T2 or T2 FLAIR weighted images (~1x1x1), these can be used to refine the pial surface. If you want to ignore these, specify None or  T1only to base surfaces on the T1 alone.", "id": "refine_pial", "name": "refine_pial", "optional": true, "type": "String", "value-choices": ["T2", "FLAIR", "None", "T1only"], "value-key": "[REFINE_PIAL]"}, {"command-line-flag": "--hires_mode", "default-value": "auto", "description": "Submilimiter (high resolution) processing. 'auto' - use only if <1.0mm data detected, 'enable' - force on, 'disable' - force off", "id": "hires_mode", "name": "hires_mode", "optional": true, "type": "String", "value-choices": ["auto", "enable", "disable"], "value-key": "[HIRES_MODE]"}, {"command-line-flag": "--parcellations", "default-value": ["aparc"], "description": "Group2 option: cortical parcellation(s) to extract stats from.", "id": "parcellations", "list": true, "name": "parcellations", "optional": true, "type": "String", "value-choices": ["aparc", "aparc.a2009s"], "value-key": "[PARCELLATIONS]"}, {"command-line-flag": "--measurements", "default-value": ["thickness"], "description": "Group2 option: cortical measurements to extract stats for.", "id": "measurements", "list": true, "name": "measurements", "optional": true, "type": "String", "value-choices": ["area", "volume", "thickness", "thicknessstd", "meancurv", "gauscurv", "foldind", "curvind"], "value-key": "[MEASUREMENTS]"}, {"command-line-flag": "-v", "default-value": "==SUPPRESS==", "description": "show program's version number and exit", "id": "version", "name": "version", "optional": true, "type": "String", "value-key": "[VERSION]"}, {"command-line-flag": "--bids_validator_config", "description": "JSON file specifying configuration of bids-validator: See https://github.com/INCF/bids-validator for more info", "id": "bids_validator_config", "name": "bids_validator_config", "optional": true, "type": "String", "value-key": "[BIDS_VALIDATOR_CONFIG]"}, {"command-line-flag": "--skip_bids_validator", "description": "skips bids validation", "id": "skip_bids_validator", "name": "skip_bids_validator", "optional": true, "type": "Flag", "value-key": "[SKIP_BIDS_VALIDATOR]"}, {"command-line-flag": "--3T", "default-value": "true", "description": "enables the two 3T specific options that recon-all supports: nu intensity correction params, and the special schwartz atlas", "id": "3T", "name": "3T", "optional": true, "type": "String", "value-choices": ["true", "false"], "value-key": "[3T]"}, {"description": "Directory containing the output of the participants analysis.", "id": "participant_level_analysis_dir", "name": "Participants dir", "optional": true, "type": "File", "value-key": "[OUTPUT_DIR]"}], "invocationschema": {"$schema": "http://json-schema.org/draft-04/schema#", "additionalProperties": false, "allOf": [{"anyOf": [{"required": ["output_dir"]}, {"required": ["participant_level_analysis_dir"]}]}], "dependencies": {"output_dir": {"properties": {"participant_level_analysis_dir": {"not": {}}}}, "participant_level_analysis_dir": {"properties": {"output_dir": {"not": {}}}}}, "description": "Invocation schema for tool name.", "properties": {"3T": {"enum": ["true", "false"]}, "acquisition_label": {"type": "string"}, "analysis_level": {"enum": ["participant", "group1", "group2"]}, "bids_dir": {"type": "string"}, "bids_validator_config": {"type": "string"}, "hires_mode": {"enum": ["auto", "enable", "disable"]}, "license_file": {"type": "string"}, "measurements": {"items": {"enum": ["area", "volume", "thickness", "thicknessstd", "meancurv", "gauscurv", "foldind", "curvind"]}, "type": "array"}, "multiple_sessions": {"enum": ["longitudinal", "multiday"]}, "n_cpus": {"type": "number"}, "output_dir": {"type": "string"}, "parcellations": {"items": {"enum": ["aparc", "aparc.a2009s"]}, "type": "array"}, "participant_label": {"items": {"type": "string"}, "type": "array"}, "participant_level_analysis_dir": {"type": "string"}, "refine_pial": {"enum": ["T2", "FLAIR", "None", "T1only"]}, "refine_pial_acquisition_label": {"type": "string"}, "session_label": {"items": {"type": "string"}, "type": "array"}, "skip_bids_validator": {"type": "boolean"}, "stages": {"items": {"enum": ["autorecon1", "autorecon2", "autorecon2-cp", "autorecon2-wm", "autorecon-pial", "autorecon3", "autorecon-all", "all"]}, "type": "array"}, "steps": {"items": {"enum": ["cross-sectional", "template", "longitudinal"]}, "type": "array"}, "template_name": {"type": "string"}, "version": {"type": "string"}}, "required": ["bids_dir", "analysis_level", "license_file"], "title": "tool name.invocationSchema", "type": "object"}, "name": "BIDS App - FreeSurfer 6.0", "suggestedresources": {"cpu-cores": 1, "ram": 1, "walltime-estimate": 60}, "toolversion": "v6.0.0", "ark_id": "https://n2t.net/ark:/70798/p72vqhk1h694q9cz37", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.1451001", "title": "BIDS app example", "description": "See https://github.com/BIDS-Apps/example", "publicationdate": "2018-10-08", "deprecated": false, "downloads": 3108, "author": "chrisfilo and others", "version": "dev", "doi": "10.5281/zenodo.1451001", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "testing"]}, "commandline": "mkdir -p OUTPUT_DIR; /run.py BIDS_DIR OUTPUT_DIR ANALYSIS_LEVEL PARTICIPANT_LABEL SESSION_LABEL", "containerimage": {"image": "bids/example", "type": "docker"}, "descriptorurl": "https://github.com/BIDS-Apps/example/blob/master/boutiques/bids-app-example.json", "groups": [{"description": "For a participants analysis, an output directory name must be specified. For a group analysis, a directory containing the output of participant-level analyses must be selected. ", "id": "output_directory", "members": ["output_dir_name", "participant_level_analysis_dir"], "mutually-exclusive": true, "name": "Output Directory", "one-is-required": true}], "inputs": [{"description": "The directory with the input dataset formatted according to the BIDS standard.", "id": "bids_dir", "name": "BIDS directory", "optional": false, "type": "File", "value-key": "BIDS_DIR"}, {"description": "The directory where the output files should be stored. If you are running a group level analysis, this folder should be prepopulated with the results of the participant level analysis.", "id": "output_dir_name", "name": "Output directory name", "optional": true, "type": "String", "value-key": "OUTPUT_DIR"}, {"description": "Directory containing the output of the participants analysis.", "id": "participant_level_analysis_dir", "name": "Participants dir", "optional": true, "type": "File", "value-key": "OUTPUT_DIR"}, {"description": "Level of the analysis that will be performed. Multiple participant level analyses can be run independently (in parallel).", "id": "analysis_level", "name": "Analysis level", "type": "String", "value-choices": ["participant", "group"], "value-key": "ANALYSIS_LEVEL"}, {"command-line-flag": "--participant_label", "description": "The label(s) of the participant(s) that should be analyzed. The label corresponds to sub-<participant_label> from the BIDS spec (so it does not include \"sub-\"). If this parameter is not provided all subjects will be analyzed. Multiple participants can be specified with a space separated list.", "id": "participant_label", "list": true, "name": "Participant label", "optional": true, "type": "String", "value-key": "PARTICIPANT_LABEL"}, {"command-line-flag": "--session_label", "description": "The label(s) of the session(s) that should be analyzed. The label corresponds to ses-<session_label>, an extension of the BIDS spec (so it does not include \"ses-\"). If this parameter is not provided all sessions will be analyzed. Multiple sessions can be specified with a space separated list.", "id": "session_label", "list": true, "name": "Session label", "optional": true, "type": "String", "value-key": "SESSION_LABEL"}], "invocationschema": {"$schema": "http://json-schema.org/draft-04/schema#", "additionalProperties": false, "allOf": [{"anyOf": [{"required": ["output_dir_name"]}, {"required": ["participant_level_analysis_dir"]}]}], "dependencies": {"output_dir_name": {"properties": {"participant_level_analysis_dir": {"not": {}}}}, "participant_level_analysis_dir": {"properties": {"output_dir_name": {"not": {}}}}}, "description": "Invocation schema for example.", "properties": {"analysis_level": {"enum": ["participant", "group", "session"]}, "bids_dir": {"type": "string"}, "output_dir_name": {"type": "string"}, "participant_label": {"items": {"type": "string"}, "type": "array"}, "participant_level_analysis_dir": {"type": "string"}, "session_label": {"items": {"type": "string"}, "type": "array"}}, "required": ["bids_dir", "analysis_level"], "title": "example.invocationSchema", "type": "object"}, "name": "BIDS app example", "outputfiles": [{"description": "The directory where the output files should be stored. If you are running a group level analysis, this folder should be prepopulated with the results of the participant level analysis.", "id": "output_dir", "name": "Output directory", "optional": false, "path-template": "OUTPUT_DIR"}], "toolversion": "dev", "ark_id": "https://n2t.net/ark:/70798/p7f4nmp503z7b0k314", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.1445789", "title": "ICA_AROMA", "description": "ICA-AROMA (i.e. Independent Component Analyis-based Automatic Removal Of Motion Artifacts) is a data-driven method to identify and remove motion-related independent components from fMRI data.", "publicationdate": "2018-10-04", "deprecated": false, "downloads": 3096, "author": "Maarten Mennes", "version": "0.3.1", "doi": "10.5281/zenodo.1445789", "schemaversion": "0.5", "container": "docker", "tags": {"domain": "fmri"}, "toolversion": "0.3.1", "name": "ICA_AROMA", "commandline": "python /ICA-AROMA/ica-aroma-wrapper.py [OUTPUT_DIR] [INPUT_FILE] [AFFINE_FILE] [WARP_FILE] [REALIGNMENT_FILE] [MASK_FILE] [MELODIC_DIR] [FEAT_DIR] [TR_NUM] [DIMS_NUM] [DENOISING_STRATEGY]", "inputs": [{"command-line-flag": "-out", "description": "Output directory name.", "default-value": "AROMA_output", "value-key": "[OUTPUT_DIR]", "type": "String", "list": false, "optional": false, "id": "outdir", "name": "Output directory"}, {"command-line-flag": "-in", "description": "Input file name of fMRI data (.nii.gz).", "value-key": "[INPUT_FILE]", "type": "File", "list": false, "requires-inputs": ["realignment_file", "affine_file", "warp_file"], "optional": true, "id": "infile", "name": "Input file"}, {"command-line-flag": "-affmat", "description": "File name of the mat-file describing the affine registration (e.g. FSL FLIRT) of the functional data to structural space (.mat file).", "value-key": "[AFFINE_FILE]", "type": "File", "list": false, "requires-inputs": ["infile"], "optional": true, "id": "affine_file", "name": "Affine registration file"}, {"command-line-flag": "-warp", "description": "File name of the warp-file describing the non-linear registration (e.g. FSL FNIRT) of the structural data to MNI152 space (.nii.gz format).", "value-key": "[WARP_FILE]", "type": "File", "list": false, "requires-inputs": ["infile"], "optional": true, "id": "warp_file", "name": "Non-linear registration warp file"}, {"command-line-flag": "-mc", "description": "File name of the text file containing the six (column-wise) realignment parameters time-courses derived from volume-realignment (e.g. MCFLIRT). (Usually .par format).", "value-key": "[REALIGNMENT_FILE]", "type": "File", "list": false, "requires-inputs": ["infile"], "optional": true, "id": "realignment_file", "name": "Realignment file"}, {"command-line-flag": "-mask", "description": "Input fMRI data should be masked (i.e. brain-extracted) or a specific mask has to be specified (-m, -mask) when running ICA-AROMA. Note the mask determined by FEAT is not recommended to be used; rather, a mask can be created via the Brain Extraction Tool of FSL (e.g. bet input output -f 0.3 -n -m -R). Not strictly required in generic mode. (Usually .nii.gz format.)", "value-key": "[MASK_FILE]", "type": "File", "list": false, "requires-inputs": ["infile"], "optional": true, "id": "mask_file", "name": "Mask file"}, {"command-line-flag": "-md", "description": "When you have already run MELODIC you can specify the melodic directory as additional input to avoid running MELODIC again. Note that MELODIC should have been run on the fMRI data prior to temporal filtering and after spatial smoothing. Further, unless you have a good reason for doing otherwise, we advise to run MELODIC as part of ICA-AROMA so that it runs with optimal settings. (Usually .ica extension.)", "value-key": "[MELODIC_DIR]", "type": "File", "list": false, "optional": true, "id": "melodic_dir", "name": "Melodic directory"}, {"command-line-flag": "-feat", "description": "Runs ICA-AROMA in post-FEAT mode. In this case, only the FEAT directory has to be specified, as well as an output directory. ICA-AROMA will automatically define the appropriate files, create an appropriate mask (see ICA-AROMA manual, section 4.1) and use the melodic.ica directory if available, in case \u2018MELODIC ICA data exploration\u2019 was checked in FEAT. (.feat extension.)", "value-key": "[FEAT_DIR]", "type": "File", "list": false, "disables-inputs": ["realignment_file", "affine_file", "warp_file", "mask_file"], "optional": true, "id": "feat_dir", "name": "FEAT directory"}, {"command-line-flag": "-tr", "description": "TR in seconds. If this is not specified the TR will be extracted from the header of the fMRI file using \u2018fslinfo\u2019. In that case, make sure the TR in the header is correct!", "value-key": "[TR_NUM]", "type": "Number", "list": false, "minimum": 0, "optional": true, "id": "tr_num", "name": "TR"}, {"command-line-flag": "-dim", "description": "Dimensionality reduction into a defined number of dimensions when running MELODIC (default is 0; automatic estimation).", "value-key": "[DIMS_NUM]", "type": "Number", "list": false, "minimum": 0, "integer": true, "optional": true, "id": "dims_num", "name": "Dimensionality reduction level"}, {"command-line-flag": "-den", "description": "Type of denoising strategy (default is nonaggr). Can be \"no\" (only classification, no denoising), \"nonaggr\" (non-aggressive denoising, i.e. partial component regression; default), \"aggr\" (aggressive denoising, i.e. full component regression), \"both\" (both aggressive and non-aggressive denoising, two outputs).", "value-key": "[DENOISING_STRATEGY]", "optional": true, "list": false, "value-choices": ["no", "nonaggr", "aggr", "both"], "type": "String", "id": "denoising_strategy", "name": "Denoising strategy"}], "containerimage": {"index": "index.docker.io", "image": "mcin/ica-aroma:latest", "type": "docker"}, "groups": [{"description": "Either input a .nii.gz file or a Feat directory. The former allows running ICA-AROMA in generic mode; the latter runs it in Feat mode.", "one-is-required": true, "mutually-exclusive": true, "members": ["infile", "feat_dir"], "id": "input_data_group", "name": "Input Data"}, {"description": "Input files used in generic mode. The realignment, affine registration, and warp files are required in this mode.", "id": "generic_mode_group", "members": ["realignment_file", "affine_file", "warp_file", "mask_file"], "name": "Generic Mode Parameters"}, {"description": "Optional parameters that can be specified in either mode of ICA-AROMA.", "id": "optional_args_group", "members": ["tr_num", "denoising_strategy", "dims_num", "melodic_dir"], "name": "Optional Parameters"}], "outputfiles": [{"description": "A folder containing the output files for ICA-AROMA (see ICA-AROMA manual, sec. 6). Should include a denoised fMRI data file (.nii.gz), text files indicating classification and feature results, and Melodic-related files (spatial maps in .nii.gz, a mask in .nii.gz, and the .ica output directory).", "list": false, "id": "folder_out", "optional": false, "path-template": "[OUTPUT_DIR]", "name": "Output folder"}], "suggestedresources": {"walltime-estimate": 5000}, "ark_id": "https://n2t.net/ark:/70798/p775msdhz1zh681jrq", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.1450997", "title": "FreeSurferPipelineBatch-CentOS7", "description": "FreeSurferPipelineBatch HCP pipeline", "publicationdate": "2018-10-08", "deprecated": false, "downloads": 3092, "author": "Washington University", "version": "3.19.0-centos7", "doi": "10.5281/zenodo.1450997", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "mri"]}, "toolversion": "3.19.0-centos7", "name": "FreeSurferPipelineBatch-CentOS7", "descriptorurl": "https://github.com/big-data-lab-team/cbrain-plugins-hcp/blob/master/cbrain_task_descriptors/freesurfer-exec-centos7-freesurferbuild-centos4.json", "commandline": "freesurfer-command-line-script.sh [SUBJECT_FOLDER] [NAME] [LICENSE]", "inputs": [{"description": "HCP subject folder, downloaded from http://www.humanconnectome.org/documentation/S500.", "value-key": "[SUBJECT_FOLDER]", "type": "File", "optional": false, "id": "subject_folder", "name": "HCP subject folder"}, {"description": "Use this parameter to give a name to the execution. Example: \"Exec-CentOS7-FreeSurferbuild-CentOS4\". The results will be written in a folder named [SUBJECT]-[EXECUTION-NAME] (a unique identifier will be appended in case a file with the same name already exists).", "default-value": "Exec-CentOS-[X]-FreeSurferbuild-CentOS-[Y]", "value-key": "[NAME]", "optional": false, "type": "String", "id": "execution_name", "name": "Execution name"}, {"description": "Use this parameter to add the content of the license file in the freesurfer directory", "default-value": "", "value-key": "[LICENSE]", "optional": false, "type": "File", "id": "freesurfer_license", "name": "FreeSurfer License"}], "containerimage": {"image": "bigdatalabteam/hcp-prefreesurfer:exec-centos7.freesurferbuild-centos4-latest", "type": "docker"}, "outputfiles": [{"path-template": "[SUBJECT_FOLDER]-[NAME]", "description": "This directory will contain 3 directories (T1w, T2w and MNINonLinear), a monitoring file (monitor.txt) and the input data.", "optional": false, "id": "results", "name": "Results"}], "suggestedresources": {"walltime-estimate": 25200}, "ark_id": "https://n2t.net/ark:/70798/p7f30jtd1022f2jtg9", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.1450999", "title": "ndmg", "description": "dwi connectome estimation pipeline", "publicationdate": "2018-10-08", "deprecated": false, "downloads": 3086, "author": "Greg Kiar", "version": "v0.1.0", "doi": "10.5281/zenodo.1450999", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "dmri"]}, "toolversion": "v0.1.0", "name": "ndmg", "descriptorurl": "https://github.com/neurodata/boutiques-tools/blob/8d5274754e2d5b3b146f2b3cc581400b96bb6081/cbrain_task_descriptors/ndmg-docker.json", "commandline": "ndmg_pipeline [DTI] [BVAL] [BVEC] [MPRAGE] [ATLAS] [MASK] [OUTDIR] [DESIKAN] [JHU] [TALAIRACH] [AAL] [HARVARDOXFORD] [CPAC200] [CLEAN]", "inputs": [{"value-key": "[DTI]", "optional": false, "type": "File", "id": "dti_file", "name": "Diffusion Tensor Image"}, {"value-key": "[BVAL]", "optional": false, "type": "File", "id": "bval_file", "name": "B-values file"}, {"value-key": "[BVEC]", "optional": false, "type": "File", "id": "bvec_file", "name": "Gradient vectors file"}, {"value-key": "[MPRAGE]", "optional": false, "type": "File", "id": "mprage_file", "name": "Structural scan file"}, {"name": "Atlas image (MNI152)", "value-key": "[ATLAS]", "type": "String", "value-choices": ["/ndmg_atlases/atlas/MNI152_T1_1mm.nii.gz"], "optional": false, "id": "atlas"}, {"name": "Atlas brain mask", "value-key": "[MASK]", "type": "String", "value-choices": ["/ndmg_atlases/atlas/MNI152_T1_1mm_brain_mask.nii.gz"], "optional": false, "id": "mask"}, {"value-key": "[OUTDIR]", "optional": false, "type": "String", "id": "outdir", "name": "Output directory"}, {"name": "Desikan parcellation", "value-key": "[DESIKAN]", "type": "String", "value-choices": ["/ndmg_atlases/labels/desikan.nii.gz"], "optional": true, "id": "desikan"}, {"name": "JHU parcellation", "value-key": "[JHU]", "type": "String", "value-choices": ["/ndmg_atlases/labels/JHU.nii.gz"], "optional": true, "id": "jhu"}, {"name": "Talairach parcellation", "value-key": "[TALAIRACH]", "type": "String", "value-choices": ["/ndmg_atlases/labels/Talairach.nii.gz"], "optional": true, "id": "talairach"}, {"name": "AAL parcellation", "value-key": "[AAL]", "type": "String", "value-choices": ["/ndmg_atlases/labels/AAL.nii.gz"], "optional": true, "id": "aal"}, {"name": "Harvard-Oxford parcellation", "value-key": "[HARVARDOXFORD]", "type": "String", "value-choices": ["/ndmg_atlases/labels/HarvardOxford.nii.gz"], "optional": true, "id": "harvardoxford"}, {"name": "CPAC200 parcellation", "value-key": "[CPAC200]", "type": "String", "value-choices": ["/ndmg_atlases/labels/CPAC200.nii.gz"], "optional": true, "id": "cpac200"}, {"command-line-flag": "-c", "name": "Clean-up flag", "value-key": "[CLEAN]", "type": "Flag", "optional": true, "id": "clean"}], "containerimage": {"index": "index.docker.io", "image": "neurodata/ndmg:v0.1.0", "type": "docker"}, "groups": [{"one-is-required": true, "id": "parcellation_group", "members": ["desikan", "jhu", "talairach", "aal", "harvardoxford", "cpac200"], "name": "Group of all used parcellations"}], "outputfiles": [{"path-template": "[OUTDIR]/reg_dti/[DTI]_aligned.nii.gz", "optional": true, "id": "aligned_dti", "path-template-stripped-extensions": [".nii", ".nii.gz"], "name": "Aligned DTI volume"}, {"path-template": "[OUTDIR]/tensors/[DTI]_tensors.npz", "optional": true, "id": "tensors", "path-template-stripped-extensions": [".nii", ".nii.gz"], "name": "Tensor maps"}, {"path-template": "[OUTDIR]/fibers/[DTI]_fibers.npz", "optional": true, "id": "fibers", "path-template-stripped-extensions": [".nii", ".nii.gz"], "name": "Fiber streamlines"}, {"path-template": "[OUTDIR]/graphs/desikan/[DTI]_desikan.gpickle", "optional": true, "id": "desikan_graph", "path-template-stripped-extensions": [".nii", ".nii.gz"], "name": "Desikan graph"}, {"path-template": "[OUTDIR]/graphs/JHU/[DTI]_JHU.gpickle", "optional": true, "id": "jhu_graph", "path-template-stripped-extensions": [".nii", ".nii.gz"], "name": "JHU graph"}, {"path-template": "[OUTDIR]/graphs/Talairach/[DTI]_Talairach.gpickle", "optional": true, "id": "talairach_graph", "path-template-stripped-extensions": [".nii", ".nii.gz"], "name": "Talairach graph"}, {"path-template": "[OUTDIR]/graphs/AAL/[DTI]_AAL.gpickle", "optional": true, "id": "aal_graph", "path-template-stripped-extensions": [".nii", ".nii.gz"], "name": "AAL graph"}, {"path-template": "[OUTDIR]/graphs/HarvardOxford/[DTI]_HarvardOxford.gpickle", "optional": true, "id": "harvardoxford_graph", "path-template-stripped-extensions": [".nii", ".nii.gz"], "name": "Harvard-Oxford graph"}, {"path-template": "[OUTDIR]/graphs/CPAC200/[DTI]_CPAC200.gpickle", "optional": true, "id": "cpac200_graph", "path-template-stripped-extensions": [".nii", ".nii.gz"], "name": "CPAC200 graph"}], "suggestedresources": {"walltime-estimate": 7400}, "ark_id": "https://n2t.net/ark:/70798/p77fpfzms5n1h44mm1", "platforms": [{"img": "/static/img/run_on_cbrain_green.png", "uri": "/cbrainredirect?cbrainurl=https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id%3D73"}]}, {"id": "zenodo.2587157", "title": "blast_formatter", "description": "Stand-alone BLAST formatter client, version 2.7.1+", "publicationdate": "2019-03-07", "deprecated": false, "downloads": 3084, "author": "Altschul et al.", "version": "v2.7.1", "doi": "10.5281/zenodo.2587157", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["bioinformatics", "blast"]}, "toolversion": "v2.7.1", "commandline": "init_genpipes -a /tmp/$USER/cvmfs-cache -c /etc/parrot/ /cvmfs/soft.mugqic/CentOS6/software/blast/ncbi-blast-2.7.1+/bin/blast_formatter [RID] [ARCHIVE] [OUTFORMAT] [fSHOWGIS] [NUM_DESCRIPTIONS] [NUM_ALIGNMENTS] [LINE_LENGTH] [fHTML] [MAX_TARGET_SEQS] [OUT] [fPARSE_DEFLINES]", "containerimage": {"index": "docker://", "image": "c3genomics/genpipes", "type": "singularity"}, "inputs": [{"command-line-flag": "-show_gis", "description": "Show NCBI GIs in deflines?", "value-key": "[fSHOWGIS]", "optional": true, "type": "Flag", "id": "show_gis", "name": "Show NCBI GIs"}, {"command-line-flag": "-html", "description": "Produce HTML Output", "value-key": "[fHTML]", "optional": true, "type": "Flag", "id": "html", "name": "Show HTML"}, {"command-line-flag": "-parse_deflines", "description": "Should the query and subject defline(s) be parsed?", "value-key": "[fPARSE_DEFLINES]", "optional": true, "type": "Flag", "id": "parse_deflines", "name": "Parse Deflines"}, {"command-line-flag": "-rid", "description": "BLAST Request ID (RID)", "disables-inputs": ["archive"], "optional": true, "value-key": "[RID]", "type": "String", "id": "rid", "name": "BLAST Request ID"}, {"command-line-flag": "-archive", "description": "File containing BLAST Archive format in ASN.1 (i.e.: output format 11)", "value-key": "[ARCHIVE]", "optional": true, "type": "File", "id": "archive", "name": "Blast Archive File"}, {"command-line-flag": "-outfmt", "description": "   alignment view options:\n     0 = Pairwise,\n     1 = Query-anchored showing identities,\n     2 = Query-anchored no identities,\n     3 = Flat query-anchored showing identities,\n     4 = Flat query-anchored no identities,\n     5 = BLAST XML,\n     6 = Tabular,\n     7 = Tabular with comment lines,\n     8 = Seqalign (Text ASN.1),\n     9 = Seqalign (Binary ASN.1),\n    10 = Comma-separated values,\n    11 = BLAST archive (ASN.1),\n    12 = Seqalign (JSON),\n    13 = Multiple-file BLAST JSON,\n    14 = Multiple-file BLAST XML2,\n    15 = Single-file BLAST JSON,\n    16 = Single-file BLAST XML2,\n    17 = Sequence Alignment/Map (SAM),\n    18 = Organism Report\n\n   Options 6, 7, 10 and 17 can be additionally configured to produce\n   a custom format specified by space delimited format specifiers.\n   The supported format specifiers for options 6, 7 and 10 are:\n            qseqid means Query Seq-id\n               qgi means Query GI\n              qacc means Query accesion\n           qaccver means Query accesion.version\n              qlen means Query sequence length\n            sseqid means Subject Seq-id\n         sallseqid means All subject Seq-id(s), separated by a ';'\n               sgi means Subject GI\n            sallgi means All subject GIs\n              sacc means Subject accession\n           saccver means Subject accession.version\n           sallacc means All subject accessions\n              slen means Subject sequence length\n            qstart means Start of alignment in query\n              qend means End of alignment in query\n            sstart means Start of alignment in subject\n              send means End of alignment in subject\n              qseq means Aligned part of query sequence\n              sseq means Aligned part of subject sequence\n            evalue means Expect value\n          bitscore means Bit score\n             score means Raw score\n            length means Alignment length\n            pident means Percentage of identical matches\n            nident means Number of identical matches\n          mismatch means Number of mismatches\n          positive means Number of positive-scoring matches\n           gapopen means Number of gap openings\n              gaps means Total number of gaps\n              ppos means Percentage of positive-scoring matches\n            frames means Query and subject frames separated by a '/'\n            qframe means Query frame\n            sframe means Subject frame\n              btop means Blast traceback operations (BTOP)\n            staxid means Subject Taxonomy ID\n          ssciname means Subject Scientific Name\n          scomname means Subject Common Name\n        sblastname means Subject Blast Name\n         sskingdom means Subject Super Kingdom\n           staxids means unique Subject Taxonomy ID(s), separated by a ';'\n                         (in numerical order)\n         sscinames means unique Subject Scientific Name(s), separated by a ';'\n         scomnames means unique Subject Common Name(s), separated by a ';'\n        sblastnames means unique Subject Blast Name(s), separated by a ';'\n                         (in alphabetical order)\n        sskingdoms means unique Subject Super Kingdom(s), separated by a ';'\n                         (in alphabetical order)\n            stitle means Subject Title\n        salltitles means All Subject Title(s), separated by a '<>'\n           sstrand means Subject Strand\n             qcovs means Query Coverage Per Subject\n           qcovhsp means Query Coverage Per HSP\n            qcovus means Query Coverage Per Unique Subject (blastn only)\n   When not provided, the default value is:\n   'qaccver saccver pident length mismatch gapopen qstart qend sstart send\n   evalue bitscore', which is equivalent to the keyword 'std'\n   The supported format specifier for option 17 is:\n                SQ means Include Sequence Data\n                SR means Subject as Reference Seq\n  Default = `0'", "value-key": "[OUTFORMAT]", "optional": true, "type": "String", "id": "outfmt", "name": "Alignment View Options"}, {"command-line-flag": "-num_descriptions", "description": "   Number of database sequences to show one-line descriptions for\n   Not applicable for outfmt > 4\n   Default = `500'", "value-key": "[NUM_DESCRIPTIONS]", "optional": true, "minimum": 0, "type": "Number", "id": "num_descriptions", "name": "Number of Sequence Descriptions to Show"}, {"command-line-flag": "-num_alignments", "description": "   Number of database sequences to show alignments for\n   Default = `250'", "value-key": "[NUM_ALIGNMENTS]", "optional": true, "minimum": 0, "type": "Number", "id": "num_alignments", "name": "Number of Sequence Alignments to Show"}, {"command-line-flag": "-line_length", "description": "   Line length for formatting alignments\n   Not applicable for outfmt > 4\n   Default = `60'", "value-key": "[LINE_LENGTH]", "optional": true, "minimum": 1, "type": "Number", "id": "line_length", "name": "Line Length"}, {"command-line-flag": "-max_target_seqs", "description": "   Maximum number of aligned sequences to keep\n   Not applicable for outfmt <= 4\n   Default = `500'", "value-key": "[MAX_TARGET_SEQS]", "optional": true, "disables-inputs": ["num_descriptions", "num_alignments"], "minimum": 1, "type": "Number", "id": "max_target_seqs", "name": "Maximum Number of Aligned Sequences to Keep"}, {"command-line-flag": "-out", "description": "   Output file name", "value-key": "[OUT]", "optional": true, "type": "String", "id": "out", "name": "Output file name"}], "outputfiles": [{"path-template": "[OUT]", "optional": false, "id": "output", "name": "Output File"}], "suggestedresources": {"walltime-estimate": 60, "ram": 1, "cpu-cores": 1}, "name": "blast_formatter", "ark_id": "https://n2t.net/ark:/70798/p7mzm0tgj4vtp29qkc", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2587156", "title": "blastdbcheck", "description": "BLAST database integrity and validity checking application", "publicationdate": "2019-03-07", "deprecated": false, "downloads": 3071, "author": "Altschul et al.", "version": "v2.7.1", "doi": "10.5281/zenodo.2587156", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["bioinformatics", "blast"]}, "inputs": [{"command-line-flag": "-dbtype", "description": "Molecule type of target db", "value-key": "[DBTYPE]", "optional": true, "value-choices": ["nucl", "prot", "guess"], "type": "String", "id": "dbtype", "name": "Database Type"}, {"command-line-flag": "-db", "description": "Specify a database name", "value-key": "[DB]", "optional": true, "type": "String", "id": "db", "name": "Database Name"}, {"command-line-flag": "-dir", "description": "Specify a directory containing one or more databases.", "disables-inputs": ["db"], "type": "String", "value-key": "[DIR]", "optional": true, "id": "dir", "name": "Database Directory"}, {"command-line-flag": "-recursive", "description": "Specify true to recurse through all dbs in directory tree.", "value-key": "[RECURSIVE]", "type": "Flag", "requires-inputs": ["dir"], "optional": true, "id": "recursive", "name": "Blast Archive File"}, {"command-line-flag": "-verbosity", "name": "Verbosity", "value-key": "[VERBOSITY]", "type": "Number", "maximum": 4, "minimum": 0, "optional": true, "id": "verbosity", "description": "Verbiosity of results.\n   0=Quiet, 1=Brief, 2=Summary, 3=Detailed, 4=Minutia"}, {"command-line-flag": "-full", "description": "If true, test every sequence (warning: may be slow).", "disables-inputs": ["stride", "random", "ends"], "type": "Flag", "value-key": "[FULL]", "optional": true, "id": "full", "name": "Full Test"}, {"command-line-flag": "-stride", "description": "Check integrity of every Nth sequence.", "value-key": "[STRIDE]", "type": "Number", "minimum": 1, "optional": true, "id": "stride", "name": "Stride Sequence Integrity Test"}, {"command-line-flag": "-random", "description": "Check this many randomly selected sequences.", "value-key": "[RANDOM]", "type": "Number", "minimum": 1, "optional": true, "id": "random", "name": "Random Sequence Test"}, {"command-line-flag": "-ends", "description": "Check this many sequences at each end of the database.", "value-key": "[ENDS]", "type": "Number", "minimum": 1, "optional": true, "id": "ends", "name": "Database End Integrity Test"}, {"command-line-flag": "-no_isam", "description": "Disable ISAM testing.", "value-key": "[NO_ISAM]", "optional": true, "type": "Flag", "id": "no_isam", "name": "NO ISAM Testing"}, {"command-line-flag": "-legacy", "description": "Enable check for existence of temporary files.", "value-key": "[LEGACY]", "optional": true, "type": "Flag", "id": "legacy", "name": "Legacy temp file existence check"}, {"command-line-flag": "-must_have_taxids", "description": "Require that all sequences in the database have taxid set.", "value-key": "[MUST_HAVE_TAXIDS]", "optional": true, "type": "Flag", "id": "must_have_taxids", "name": "Must Have taxid set"}, {"command-line-flag": "-cdd_delta", "description": "Do aditional tests for a CDD database for DELTA-BLAST", "value-key": "[CDD_DELTA]", "optional": true, "type": "Flag", "id": "cdd_delta", "name": "Do CDD database tests for DELTA-BLAST"}], "commandline": "init_genpipes -a /tmp/$USER/cvmfs-cache -c /etc/parrot/ /cvmfs/soft.mugqic/CentOS6/software/blast/ncbi-blast-2.7.1+/bin/blastdbcheck [DB] [DBTYPE] [DIR] [RECURSIVE] [VERBOSITY] [FULL] [STRIDE] [RANDOM] [ENDS] [NO_ISAM] [LEGACY] [MUST_HAVE_TAXIDS] [CDD_DELTA]", "toolversion": "v2.7.1", "containerimage": {"index": "docker://", "image": "c3genomics/genpipes", "type": "singularity"}, "suggestedresources": {"walltime-estimate": 60, "ram": 1, "cpu-cores": 1}, "name": "blastdbcheck", "ark_id": "https://n2t.net/ark:/70798/p7zgwrq0m1nr56g45f", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2541125", "title": "BEst", "description": "EEG/MEG source localisation techniques based upon the Maximum Entropy on the Mean framework", "publicationdate": "2019-01-15", "deprecated": false, "downloads": 3070, "author": "Oba\u00ef Bin Ka\u2019b Ali", "version": "1.0", "doi": "10.5281/zenodo.2541125", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": "neuroinformatics"}, "commandline": "$BEST_DIR/run_BEst.sh $MCR_ROOT [RECORDINGS] [LEADFIELD] [ADJACENCY_MATRIX] [SOURCES] [MEM_METHOD] \"[SENSOR_TYPES]\" \"[RECONSTRUCTION_WINDOW]\" \"[BASELINE_WINDOW]\" [BASELINE] [NORMALIZATION] [CLUSTERING_METHOD] [MSP_WINDOW] [MSP_THRESHOLD_METHOD] [MSP_THRESHOLD] [NEIGHBORHOOD_ORDER] [SPATIAL_SMOOTHING] [ACTIVE_MEAN_INIT] [ACTIVE_PROBA_INIT] [LAMBDA_INIT] [ACTIVE_PROBA_THRESHOLD] [ACTIVE_VAR_COEF] [INACTIVE_VAR_COEF] [NOISE_COV_METHOD] [OPTIM_METHOD] [USE_PARALLEL]", "containerimage": {"image": "MontrealSergiy/BEst", "type": "singularity"}, "name": "BEst", "inputs": [{"id": "recordings", "name": "Recording data", "type": "File", "optional": false, "value-key": "[RECORDINGS]"}, {"id": "leadfield", "name": "Lead field data", "type": "File", "optional": false, "value-key": "[LEADFIELD]"}, {"id": "adjacency_matrix", "name": "Adjacency matrix", "type": "File", "optional": false, "value-key": "[ADJACENCY_MATRIX]"}, {"id": "outfile", "name": "Output file", "description": "Name of the output file with extension '.mat'", "type": "String", "optional": false, "default-value": "sources.mat", "value-key": "[OUTFILE]"}, {"id": "mem_method", "name": "MEM method", "type": "String", "optional": false, "value-choices": ["cMEM"], "default-value": "cMEM", "value-key": "[MEM_METHOD]"}, {"id": "sensor_types", "name": "Sensor types", "description": "The data sensors types to process. If, for instance, your input recording data contains both EEG and MEG channels, then, you could choose to process only the EEG channels by setting this parameter to 'EEG'.", "type": "String", "optional": false, "list": true, "max-list-entries": 2, "min-list-entries": 1, "value-choices": ["EEG", "MEG"], "value-key": "[SENSOR_TYPES]"}, {"id": "reconstruction_window", "name": "Reconstruction time window", "description": "This is the portion of your input recording data to reconstruct.", "type": "Number", "optional": false, "list": true, "max-list-entries": 2, "min-list-entries": 2, "minimum": 0, "value-key": "[RECONSTRUCTION_WINDOW]"}, {"id": "baseline_window", "name": "Baseline time window", "description": "This is the portion of your baseline data to use for estimating a noise covariance matrix.", "type": "Number", "optional": false, "list": true, "max-list-entries": 2, "min-list-entries": 2, "minimum": 0, "value-key": "[BASELINE_WINDOW]"}, {"id": "baseline", "name": "Baseline data", "description": "This is the path to your baseline file if any. If no baseline file is specified, then the baseline data will be extracted from within the recording data.", "type": "File", "optional": true, "command-line-flag": "baseline", "value-key": "[BASELINE]"}, {"id": "normalization", "name": "Normalization", "description": "Normalization strategy used for computing the solution. If adaptive, a minimum solution is used to normalize the data.", "type": "String", "optional": true, "default-value": "adaptive", "value-choices": ["adaptive", "fixed"], "command-line-flag": "normalization", "value-key": "[NORMALIZATION]"}, {"id": "clustering_method", "name": "Clustering method", "description": "If dynamic, then the cortical parcels are computed within consecutive time windows specified with the option: MSP window. If static, then one set of cortical parcels is computed for the whole data.", "type": "String", "optional": true, "default-value": "static", "value-choices": ["static", "dynamic"], "value-disables": {"static": ["msp_window"], "dynamic": []}, "value-requires": {"static": [], "dynamic": ["msp_window"]}, "command-line-flag": "clusteringMethod", "value-key": "[CLUSTERING_METHOD]"}, {"id": "msp_window", "name": "MSP window", "description": "Used when clustering method is set to 'dynamic', this is the size of the sliding window in millisecond (ms).", "type": "Number", "optional": true, "minimum": 0, "default-value": 10, "command-line-flag": "mspWindow", "value-key": "[MSP_WINDOW]"}, {"id": "msp_threshold_method", "name": "MSP scores threshold method", "description": "Thresholding method applied to the MSP scores. If set to 'fdr' then thresholds are learned from baseline. Otherwise, the option 'MSP scores threshold' is used.", "type": "String", "optional": true, "default-value": "arbitrary", "value-choices": ["arbitrary", "fdr"], "value-disables": {"arbitrary": [], "fdr": ["msp_threshold"]}, "value-requires": {"arbitrary": ["msp_threshold"], "fdr": []}, "command-line-flag": "mspThresholdMethod", "value-key": "[MSP_THRESHOLD_METHOD]"}, {"id": "msp_threshold", "name": "MSP scores threshold", "description": "Used when MSP scores threshold method is set to 'arbitrary', whole brain parcellation is set to 0.", "type": "Number", "optional": true, "minimum": 0, "maximum": 1, "default-value": 0, "command-line-flag": "mspThreshold", "value-key": "[MSP_THRESHOLD]"}, {"id": "neighborhood_order", "name": "Neighborhood order", "description": "Sets maximal size of cortical parcels (initial source configuration for MEM).", "type": "Number", "optional": true, "integer": true, "minimum": 0, "default-value": 4, "command-line-flag": "neighborhoodOrder", "value-key": "[NEIGHBORHOOD_ORDER]"}, {"id": "spatial_smoothing", "name": "Spatial smoothing", "description": "Smoothness of MEM solution: spatial regularization of the MEM (linear decay of spatial source correlations).", "type": "Number", "optional": true, "minimum": 0, "maximum": 1, "default-value": 0.6, "command-line-flag": "spatialSmoothing", "value-key": "[SPATIAL_SMOOTHING]"}, {"id": "active_mean_init", "name": "Active mean initialization", "description": "Initialization method of the active mean of each cluster.", "type": "Number", "optional": true, "integer": true, "value-choices": [1, 2, 3, 4], "default-value": 2, "command-line-flag": "activeMeanInit", "value-key": "[ACTIVE_MEAN_INIT]"}, {"id": "active_proba_init", "name": "Active probability initialization", "description": "Initialization method of the active probability of each cluster.", "type": "Number", "optional": true, "integer": true, "value-choices": [1, 2, 3, 4, 5], "default-value": 3, "command-line-flag": "activeProbaInit", "value-key": "[ACTIVE_PROBA_INIT]"}, {"id": "lambda_init", "name": "Lambda initialization", "description": "Initialization method of the sensor weights vector.", "type": "Number", "optional": true, "integer": true, "value-choices": [0, 1], "default-value": 1, "command-line-flag": "lambdaInit", "value-key": "[LAMBDA_INIT]"}, {"id": "active_proba_threshold", "name": "Active probability threshold", "description": "Used to exclude clusters with low probability from the computed solution.", "type": "Number", "optional": true, "minimum": 0, "maximum": 1, "default-value": 0, "command-line-flag": "activeProbaThreshold", "value-key": "[ACTIVE_PROBA_THRESHOLD]"}, {"id": "active_var_coef", "name": "Active variance coefficient", "description": "A weight applied to the active variance of each cluster.", "type": "Number", "optional": true, "minimum": 0, "maximum": 1, "default-value": 0.05, "command-line-flag": "activeVarCoef", "value-key": "[ACTIVE_VAR_COEF]"}, {"id": "inactive_var_coef", "name": "Inactive variance coefficient", "description": "A weight applied to the inactive variance of each cluster.", "type": "Number", "optional": true, "minimum": 0, "maximum": 1, "default-value": 0, "command-line-flag": "inactiveVarCoef", "value-key": "[INACTIVE_VAR_COEF]"}, {"id": "noise_cov_method", "name": "Noise covariance method", "description": "The performance of the MEM is tied to a consistent estimation of the noise covariance matrix. We recommend using the 'diagonal' method.", "type": "Number", "optional": true, "integer": true, "value-choices": [0, 1, 2, 3, 4], "default-value": 2, "command-line-flag": "noiseCovMethod", "value-key": "[NOISE_COV_METHOD]"}, {"id": "optim_method", "name": "Optimization routine", "description": "'fminunc': MATLAB standard unconstrained optimization (optimization toolbox required). 'minFunc': Unconstrained optimization, copyright Mark Schmidt, INRIA.", "type": "String", "optional": true, "default-value": "fminunc", "value-choices": ["fminunc", "minfunc"], "command-line-flag": "optimMethod", "value-key": "[OPTIM_METHOD]"}, {"id": "use_parallel", "name": "Parallel computing", "description": "0: default - false, 1: true", "type": "Number", "optional": true, "integer": true, "value-choices": [0, 1], "default-value": 0, "command-line-flag": "useParallel", "value-key": "[USE_PARALLEL]"}], "outputfiles": [{"id": "sources", "name": "Sources", "path-template": "[OUTFILE].mat", "path-template-stripped-extensions": [".mat"], "optional": false, "value-key": "[SOURCES]"}], "groups": [{"id": "data_definition", "name": "Data definition", "members": ["sensor_types", "reconstruction_window", "baseline", "baseline_window", "normalization"]}, {"id": "clustering", "name": "Clustering", "members": ["clustering_method", "msp_window", "msp_threshold_method", "msp_threshold", "neighborhood_order", "spatial_smoothing"]}, {"id": "model_priors", "name": "Model priors", "members": ["active_mean_init", "active_proba_init", "lambda_init", "active_proba_threshold", "active_var_coef", "inactive_var_coef"]}, {"id": "solver_options", "name": "Solver options", "members": ["noise_cov_method", "optim_method", "use_parallel"]}], "toolversion": "1.0", "ark_id": "https://n2t.net/ark:/70798/p7cp7f92v5crv0g4g4", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.1450993", "title": "PostFreeSurferPipelineBatch-CentOS7", "description": "PostFreeSurferPipelineBatch HCP pipeline", "publicationdate": "2018-10-08", "deprecated": false, "downloads": 3069, "author": "Washington University", "version": "3.19.0-centos7", "doi": "10.5281/zenodo.1450993", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "mri"]}, "toolversion": "3.19.0-centos7", "name": "PostFreeSurferPipelineBatch-CentOS7", "descriptorurl": "https://github.com/big-data-lab-team/cbrain-plugins-hcp/blob/master/cbrain_task_descriptors/postfreesurfer-exec-centos7.json", "commandline": "postfreesurfer-command-line-script.sh [SUBJECT_FOLDER] [NAME] [LICENSE]", "inputs": [{"description": "HCP subject folder, downloaded from http://www.humanconnectome.org/documentation/S500.", "value-key": "[SUBJECT_FOLDER]", "type": "File", "optional": false, "id": "subject_folder", "name": "HCP subject folder"}, {"description": "Use this parameter to give a name to the execution. Example: \"Exec-CentOS5-PostFreeSurfer\". The results will be written in a folder named [SUBJECT]-[EXECUTION-NAME] (a unique identifier will be appended in case a file with the same name already exists).", "default-value": "Exec-CentOS-[X]-PostFreeSurfer", "value-key": "[NAME]", "optional": false, "type": "String", "id": "execution_name", "name": "Execution name"}, {"description": "Use this parameter to add the content of the license file in the freesurfer directory", "default-value": "", "value-key": "[LICENSE]", "optional": false, "type": "File", "id": "freesurfer_license", "name": "FreeSurfer License"}], "containerimage": {"image": "bigdatalabteam/hcp-prefreesurfer:exec-centos7.freesurferbuild-centos4-latest", "type": "docker"}, "outputfiles": [{"path-template": "[SUBJECT_FOLDER]-[NAME]", "description": "This directory will contain 3 directories (T1w, T2w and MNINonLinear), a monitoring file (monitor.txt) and the input data.", "optional": false, "id": "results", "name": "Results"}], "suggestedresources": {"walltime-estimate": 25200}, "ark_id": "https://n2t.net/ark:/70798/p7w5sv39w067905js3", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2636973", "title": "BrainExtraction", "description": "BrainExtraction, as implemented in Nipype (module: nipype.interfaces.ants, interface: BrainExtraction).", "publicationdate": "2019-04-12", "deprecated": false, "downloads": 3064, "author": "Nipype (interface), Brian B. Avants et al. (tool)", "version": "1.0.0", "doi": "10.5281/zenodo.2636973", "schemaversion": "0.5", "container": "docker", "tags": {"domain": "neuroinformatics", "source": "nipype-interface"}, "name": "BrainExtraction", "commandline": "${ANTSPATH}/antsBrainExtraction.sh [ANATOMICAL_IMAGE] [BRAIN_PROBABILITY_MASK] [BRAIN_TEMPLATE] [DEBUG] [DIMENSION] [EXTRACTION_REGISTRATION_MASK] [IMAGE_SUFFIX] [KEEP_TEMPORARY_FILES] [OUT_PREFIX] [USE_FLOATINGPOINT_PRECISION] [USE_RANDOM_SEEDING]", "url": "https://github.com/nipy/nipype/blob/master/nipype/interfaces/ants/segmentation.py", "inputs": [{"id": "anatomical_image", "name": "Anatomical image", "type": "File", "value-key": "[ANATOMICAL_IMAGE]", "command-line-flag": "-a", "description": "An existing file name. Structural image, typically t1.  if more than one anatomical image is specified, subsequently specified images are used during the segmentation process.  however, only the first image is used in the registration of priors. our suggestion would be to specify the t1 as the first image. anatomical template created using e.g. lpba40 data set with buildtemplateparallel.sh in ants.", "optional": false}, {"id": "brain_probability_mask", "name": "Brain probability mask", "type": "File", "value-key": "[BRAIN_PROBABILITY_MASK]", "command-line-flag": "-m", "description": "An existing file name. Brain probability mask created using e.g. lpba40 data set which have brain masks defined, and warped to anatomical template and averaged resulting in a probability image.", "optional": false}, {"id": "brain_template", "name": "Brain template", "type": "File", "value-key": "[BRAIN_TEMPLATE]", "command-line-flag": "-e", "description": "An existing file name. Anatomical template created using e.g. lpba40 data set with buildtemplateparallel.sh in ants.", "optional": false}, {"id": "debug", "name": "Debug", "type": "Flag", "value-key": "[DEBUG]", "command-line-flag": "-z 1", "description": "A boolean. If > 0, runs a faster version of the script. only for testing. implies -u 0. requires single thread computation for complete reproducibility.", "optional": true}, {"id": "dimension", "name": "Dimension", "type": "Number", "value-key": "[DIMENSION]", "command-line-flag": "-d", "description": "3 or 2. Image dimension (2 or 3).", "optional": true, "default-value": 3, "integer": true, "value-choices": [3, 2]}, {"id": "extraction_registration_mask", "name": "Extraction registration mask", "type": "File", "value-key": "[EXTRACTION_REGISTRATION_MASK]", "command-line-flag": "-f", "description": "An existing file name. Mask (defined in the template space) used during registration for brain extraction. to limit the metric computation to a specific region.", "optional": true}, {"id": "image_suffix", "name": "Image suffix", "type": "String", "value-key": "[IMAGE_SUFFIX]", "command-line-flag": "-s", "description": "A unicode string. Any of standard itk formats, nii.gz is default.", "optional": true, "default-value": "nii.gz"}, {"id": "keep_temporary_files", "name": "Keep temporary files", "type": "Number", "integer": true, "value-key": "[KEEP_TEMPORARY_FILES]", "command-line-flag": "-k", "description": "An integer (int or long). Keep brain extraction/segmentation warps, etc (default = 0).", "optional": true}, {"id": "out_prefix", "name": "Out prefix", "type": "String", "value-key": "[OUT_PREFIX]", "command-line-flag": "-o", "description": "A unicode string. Prefix that is prepended to all output files (default = highress001_).", "optional": true, "default-value": "highres001_"}, {"id": "use_floatingpoint_precision", "name": "Use floatingpoint precision", "type": "Number", "value-key": "[USE_FLOATINGPOINT_PRECISION]", "command-line-flag": "-q", "description": "0 or 1. Use floating point precision in registrations (default = 0).", "optional": true, "integer": true, "value-choices": [0, 1]}, {"id": "use_random_seeding", "name": "Use random seeding", "type": "Number", "value-key": "[USE_RANDOM_SEEDING]", "command-line-flag": "-u", "description": "0 or 1. Use random number generated from system clock in atropos (default = 1).", "optional": true, "integer": true, "value-choices": [0, 1]}], "outputfiles": [{"name": "Brainextractionbrain", "id": "BrainExtractionBrain", "path-template": "[OUT_PREFIX]BrainExtractionBrain.[IMAGE_SUFFIX]", "optional": true, "description": "An existing file name. Brain extraction image."}, {"name": "Brainextractioncsf", "id": "BrainExtractionCSF", "path-template": "[OUT_PREFIX]BrainExtractionCSF.[IMAGE_SUFFIX]", "optional": true, "description": "An existing file name. Segmentation mask with only csf."}, {"name": "Brainextractiongm", "id": "BrainExtractionGM", "path-template": "[OUT_PREFIX]BrainExtractionGM.[IMAGE_SUFFIX]", "optional": true, "description": "An existing file name. Segmentation mask with only grey matter."}, {"name": "Brainextractioninitialaffine", "id": "BrainExtractionInitialAffine", "path-template": "[OUT_PREFIX]BrainExtractionInitialAffine.mat", "optional": true, "description": "An existing file name. No description provided."}, {"name": "Brainextractioninitialaffinefixed", "id": "BrainExtractionInitialAffineFixed", "path-template": "[OUT_PREFIX]BrainExtractionInitialAffineFixed.[IMAGE_SUFFIX]", "optional": true, "description": "An existing file name. No description provided."}, {"name": "Brainextractioninitialaffinemoving", "id": "BrainExtractionInitialAffineMoving", "path-template": "[OUT_PREFIX]BrainExtractionInitialAffineMoving.[IMAGE_SUFFIX]", "optional": true, "description": "An existing file name. No description provided."}, {"name": "Brainextractionlaplacian", "id": "BrainExtractionLaplacian", "path-template": "[OUT_PREFIX]BrainExtractionLaplacian.[IMAGE_SUFFIX]", "optional": true, "description": "An existing file name. No description provided."}, {"name": "Brainextractionmask", "id": "BrainExtractionMask", "path-template": "[OUT_PREFIX]BrainExtractionMask.[IMAGE_SUFFIX]", "optional": true, "description": "An existing file name. Brain extraction mask."}, {"name": "Brainextractionprior0genericaffine", "id": "BrainExtractionPrior0GenericAffine", "path-template": "[OUT_PREFIX]BrainExtractionPrior0GenericAffine.mat", "optional": true, "description": "An existing file name. No description provided."}, {"name": "Brainextractionprior1inversewarp", "id": "BrainExtractionPrior1InverseWarp", "path-template": "[OUT_PREFIX]BrainExtractionPrior1InverseWarp.[IMAGE_SUFFIX]", "optional": true, "description": "An existing file name. No description provided."}, {"name": "Brainextractionprior1warp", "id": "BrainExtractionPrior1Warp", "path-template": "[OUT_PREFIX]BrainExtractionPrior1Warp.[IMAGE_SUFFIX]", "optional": true, "description": "An existing file name. No description provided."}, {"name": "Brainextractionpriorwarped", "id": "BrainExtractionPriorWarped", "path-template": "[OUT_PREFIX]BrainExtractionPriorWarped.[IMAGE_SUFFIX]", "optional": true, "description": "An existing file name. No description provided."}, {"name": "Brainextractionsegmentation", "id": "BrainExtractionSegmentation", "path-template": "[OUT_PREFIX]BrainExtractionSegmentation.[IMAGE_SUFFIX]", "optional": true, "description": "An existing file name. Segmentation mask with csf, gm, and wm."}, {"name": "Brainextractiontemplatelaplacian", "id": "BrainExtractionTemplateLaplacian", "path-template": "[OUT_PREFIX]BrainExtractionTemplateLaplacian.[IMAGE_SUFFIX]", "optional": true, "description": "An existing file name. No description provided."}, {"name": "Brainextractiontmp", "id": "BrainExtractionTmp", "path-template": "[OUT_PREFIX]BrainExtractionTmp.[IMAGE_SUFFIX]", "optional": true, "description": "An existing file name. No description provided."}, {"name": "Brainextractionwm", "id": "BrainExtractionWM", "path-template": "[OUT_PREFIX]BrainExtractionWM.[IMAGE_SUFFIX]", "optional": true, "description": "An existing file name. Segmenration mask with only white matter."}, {"name": "N4corrected0", "id": "N4Corrected0", "path-template": "[OUT_PREFIX]N4Corrected0.[IMAGE_SUFFIX]", "optional": true, "description": "An existing file name. N4 bias field corrected image."}, {"name": "N4truncated0", "id": "N4Truncated0", "path-template": "[OUT_PREFIX]N4Truncated0.[IMAGE_SUFFIX]", "optional": true, "description": "An existing file name. No description provided."}], "toolversion": "1.0.0", "containerimage": {"image": "bt5e/ants:latest", "index": "index.docker.io", "type": "docker"}, "ark_id": "https://n2t.net/ark:/70798/p7gp3zn8120bf666rh", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2573071", "title": "GateCLforOpenDose", "description": "Descriptor for the GATE command with input parameters, used for import in VIP via Boutiques", "publicationdate": "2019-02-19", "deprecated": false, "downloads": 3064, "author": "Gilles Mathieu, using GATE application", "version": "v0.2.0", "doi": "10.5281/zenodo.2573071", "schemaversion": "0.5", "container": "None", "tags": {"application": "GATE", "domain": "nuclear medicine"}, "commandline": "unzip [INDATA]; source [GATERELEASEPATH]/env.sh [GATERELEASEPATH]; [GATERELEASEPATH]/shared_libs/ld-linux-x86-64.so.2 --library-path [GATERELEASEPATH]/root/lib:[GATERELEASEPATH]/shared_libs/ [GATERELEASEPATH]/Gate -a [Source_ID,[ORGANID]][particle,[PARTICLETYPE]][energy,[ENERGY]][nb,[NBPRIMARIES]] [MACFILE] > output.log;  tar czf [RESULTS] ./output output.log", "errorcodes": [{"code": 1, "description": "Crashed"}], "inputs": [{"command-line-flag": "", "command-line-flag-separator": "", "id": "gatereleasepath", "name": "Path to the Gate Release used by the application", "optional": false, "type": "String", "value-key": "[GATERELEASEPATH]"}, {"id": "indata", "name": "LFN of the archive containing all input data", "optional": false, "type": "File", "value-key": "[INDATA]"}, {"command-line-flag": "", "command-line-flag-separator": "", "id": "organid", "name": "Organ ID ref to the organs table", "optional": false, "type": "String", "value-key": "[ORGANID]"}, {"command-line-flag": "", "command-line-flag-separator": "", "id": "particletype", "name": "Type of Particle to simulate", "optional": false, "type": "String", "value-key": "[PARTICLETYPE]"}, {"command-line-flag": "", "command-line-flag-separator": "", "id": "energy", "name": "The level of energy to simulate", "optional": false, "type": "String", "value-key": "[ENERGY]"}, {"command-line-flag": "", "command-line-flag-separator": "", "id": "nbprimaries", "name": "The number of primaries to simulate", "optional": false, "type": "String", "value-key": "[NBPRIMARIES]"}, {"id": "macfile", "name": "The name of the main macro file", "optional": false, "type": "String", "value-key": "[MACFILE]"}], "name": "GateCLforOpenDose", "outputfiles": [{"description": "archive of the output folder containing execution results, and the output of the command", "id": "results", "name": "results", "optional": false, "path-template": "OpenDose_[ORGANID]_[PARTICLETYPE]_[ENERGY]_[NBPRIMARIES].tar.gz", "value-key": "[RESULTS]"}], "toolversion": "v0.2.0", "ark_id": "https://n2t.net/ark:/70798/p7sbf390x20kq0139n", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3308620", "title": "oneVoxel", "description": "Adds 1-voxel noise to a Nifti image at either a provided or random location within a mask.", "publicationdate": "2019-07-10", "deprecated": false, "downloads": 3061, "author": "Greg Kiar <gkiar.github.io>", "version": "v0.3.0rc3", "doi": "10.5281/zenodo.3308620", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "image processing", "mri", "noise"]}, "commandline": "onevox [IMAGE_FILE] [OUTPUT_DIRECTORY] [MASK_FILE] [NO_SCALE] [INTENSITY] [ERODE] [REPEAT] [LOCATION] [FORCE] [MODE] [CLEAN] [APPLY_NOISE] [VERBOSE] [BOUTIQUES]", "inputs": [{"optional": false, "type": "File", "id": "image_file", "description": "Nifti image to be injected with one-voxel noise. Default behaviour is that this will be done at a random location within an image mask.", "name": "image_file", "value-key": "[IMAGE_FILE]"}, {"optional": false, "type": "File", "id": "output_directory", "description": "Path for where the resulting Nifti image with one voxel noise will be stored.", "name": "output_directory", "value-key": "[OUTPUT_DIRECTORY]"}, {"description": "Nifti image containing a binary mask for the input image. The noise location will be selected randomly within this mask, unless a location is provided.", "optional": true, "command-line-flag": "--mask_file", "id": "mask_file", "name": "mask_file", "value-key": "[MASK_FILE]", "type": "File"}, {"description": "Dictates the way in which noise is aplpied to the image. If set, the value specified with the intensity flag will be set to the new value. If not set, the intensity value will be multiplied by the original image value at the location.", "optional": true, "command-line-flag": "--no_scale", "id": "scale", "name": "scale", "value-key": "[NO_SCALE]", "type": "Flag"}, {"default-value": 0.01, "command-line-flag": "--intensity", "id": "intensity", "minimum": 0, "optional": true, "description": "The intensity of the noise to be injected in the image. Default value is 0.01 so specifying the scale flag alone will result in a 1%% intensity change at the target location.", "name": "intensity", "value-key": "[INTENSITY]", "type": "Number"}, {"integer": true, "default-value": 3, "command-line-flag": "--erode", "id": "erode", "minimum": 0, "optional": true, "description": "Value dictating how much to erode the binary mask before selecting a location for noise. The default value assumes a slightly generous mask.", "name": "erode", "value-key": "[ERODE]", "type": "Number"}, {"integer": true, "default-value": 1, "command-line-flag": "--repeat", "id": "repeat", "minimum": 0, "optional": true, "description": "Value dictating how many times to generate noise in the target image. This cannot be used with the 'location' parameter.", "name": "repeat", "value-key": "[REPEAT]", "type": "Number"}, {"description": "Specifies a target location for injecting noise. This location must live within the provided mask in voxel coordinates. If not provided, a random location within the mask will be used.", "command-line-flag": "--location", "id": "location", "optional": true, "list": true, "integer": true, "name": "location", "value-key": "[LOCATION]", "type": "Number"}, {"description": "Disables checks and restrictions on noise that may be not recommended for a typical workflow. By default, locations can only be specified within the mask, but this overrides that behaviour.", "optional": true, "command-line-flag": "--force", "id": "force", "name": "force", "value-key": "[FORCE]", "type": "Flag"}, {"description": "Determines where noise will be injected in the case of higher-dimensional images than masks. 'Single' (default) will choose a single position in all higher dimensions, resulting in 1 point of noise. 'Uniform' will choose a location within the mask and apply it uniformly across all other dimensions. 'Independent' will generate a random location within the mask for each volume in the remaining dimensions, and is mutually exclusive with providing a location.", "default-value": "single", "command-line-flag": "--mode", "id": "mode", "value-choices": ["single", "uniform", "independent"], "name": "mode", "optional": true, "value-key": "[MODE]", "type": "String"}, {"description": "Deletes the noisy Nifti image from disk. This is intended to be used to save space, and the images can be regenerated using the 'apply' option and providing the associated JSON file.", "optional": true, "command-line-flag": "--clean", "id": "clean", "name": "clean", "value-key": "[CLEAN]", "type": "Flag"}, {"description": "Provided with a path to 1-voxel noise associated JSON file, will apply noise to the image. A hash is stored in this file to verify that the same noise is injected each time the file is created.", "optional": true, "command-line-flag": "--apply_noise", "id": "apply_noise", "name": "apply_noise", "value-key": "[APPLY_NOISE]", "type": "File"}, {"description": "Toggles verbose output printing.", "optional": true, "command-line-flag": "--verbose", "id": "verbose", "name": "verbose", "value-key": "[VERBOSE]", "type": "Flag"}, {"description": "Toggles creation of a Boutiques descriptor and invocation from the tool and inputs.", "optional": true, "command-line-flag": "--boutiques", "id": "boutiques", "name": "boutiques", "value-key": "[BOUTIQUES]", "type": "Flag"}], "groups": [{"members": ["mask_file", "apply_noise"], "name": "noise_position_group", "one-is-required": true, "id": "noise_position_group"}], "toolversion": "v0.3.0rc3", "containerimage": {"image": "gkiar/onevoxel:v0.3.0rc3", "index": "index.docker.io", "type": "docker"}, "outputfiles": [{"path-template-stripped-extensions": [".nii.gz", ".nii"], "name": "Noisy Image", "optional": true, "id": "noisy_image", "path-template": "[OUTPUT_DIRECTORY]*_1vox-*.nii.gz"}, {"path-template-stripped-extensions": [".nii.gz", ".nii"], "name": "Noise Summary", "optional": true, "id": "noise_summary", "path-template": "[OUTPUT_DIRECTORY]*_1vox-*.json"}], "suggestedresources": {"walltime-estimate": 20, "cpu-cores": 1, "ram": 2}, "name": "oneVoxel", "ark_id": "https://n2t.net/ark:/70798/p74d744wm1b574hxjk", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3242714", "title": "MRIQC", "description": "tool description", "publicationdate": "2019-06-10", "deprecated": false, "downloads": 3056, "author": "Plodrack lab", "version": "v0.14.2", "doi": "10.5281/zenodo.3242714", "schemaversion": "0.5", "container": "None", "tags": {"application-type": ["bids"], "domain": ["neuroinformatics", "mri"]}, "commandline": "mriqc_run.py [BIDS_DIR] [OUTPUT_DIR] [ANALYSIS_LEVEL] [VERSION] [PARTICIPANT_LABEL] [SESSION_ID] [RUN_ID] [TASK_ID] [MODALITIES] [DSNAME] [WORK_DIR] [VERBOSE_REPORTS] [WRITE_GRAPH] [DRY_RUN] [PROFILE] [USE_PLUGIN] [NO_SUB] [EMAIL] [VERBOSE_COUNT] [WEBAPI_URL] [WEBAPI_PORT] [UPLOAD_STRICT] [N_PROCS] [MEM_GB] [TESTING] [FLOAT32] [ICA] [HMC_AFNI] [HMC_FSL] [FFT_SPIKES_DETECTOR] [FD_THRES] [ANTS_NTHREADS] [ANTS_FLOAT] [ANTS_SETTINGS] [DEOBLIQUE] [DESPIKE] [START_IDX] [STOP_IDX] [CORRECT_SLICE_TIMING]", "inputs": [{"description": "The directory with the input dataset formatted according to the BIDS standard.", "id": "bids_dir", "name": "bids_dir", "optional": false, "type": "File", "value-key": "[BIDS_DIR]"}, {"description": "The directory where the output files should be stored. If you are running group level analysis this folder should be prepopulated with the results of theparticipant level analysis.", "id": "output_dir_name", "name": "output_dir_name", "optional": false, "type": "String", "value-key": "[OUTPUT_DIR]"}, {"description": "Level of the analysis that will be performed. Multiple participant level analyses can be run independently (in parallel) using the same output_dir.", "id": "analysis_level", "list": true, "name": "analysis_level", "optional": false, "type": "String", "value-choices": ["participant", "group"], "value-key": "[ANALYSIS_LEVEL]"}, {"command-line-flag": "--version", "default-value": false, "description": "show program's version number and exit", "id": "version", "name": "version", "optional": true, "type": "Flag", "value-key": "[VERSION]"}, {"command-line-flag": "--participant_label", "description": "one or more participant identifiers (the sub- prefix can be removed)", "id": "participant_label", "name": "participant_label", "optional": true, "type": "String", "value-key": "[PARTICIPANT_LABEL]"}, {"command-line-flag": "--session-id", "description": "filter input dataset by session id", "id": "session_id", "name": "session_id", "optional": true, "type": "String", "value-key": "[SESSION_ID]"}, {"command-line-flag": "--run-id", "description": "filter input dataset by run id (only integer run ids are valid)", "id": "run_id", "name": "run_id", "optional": true, "type": "Number", "value-key": "[RUN_ID]"}, {"command-line-flag": "--task-id", "description": "filter input dataset by task id", "id": "task_id", "name": "task_id", "optional": true, "type": "String", "value-key": "[TASK_ID]"}, {"command-line-flag": "-m", "description": "filter input dataset by MRI type (\"T1w\", \"T2w\", or \"bold\")", "id": "modalities", "name": "modalities", "optional": true, "list": true, "type": "String", "value-choices": ["T1w", "bold", "T2w"], "value-key": "[MODALITIES]"}, {"command-line-flag": "--dsname", "description": "a dataset name", "id": "dsname", "name": "dsname", "optional": true, "type": "String", "value-key": "[DSNAME]"}, {"command-line-flag": "-w", "default-value": "work", "description": "The folder used to store intermediate results", "id": "work_dir", "name": "work_dir", "optional": true, "type": "String", "value-key": "[WORK_DIR]"}, {"command-line-flag": "--verbose-reports", "description": "Should MRIQC print verbose reports", "id": "verbose_reports", "name": "verbose_reports", "optional": true, "type": "Flag", "value-key": "[VERBOSE_REPORTS]"}, {"command-line-flag": "--write-graph", "description": "Write workflow graph.", "id": "write_graph", "name": "write_graph", "optional": true, "type": "Flag", "value-key": "[WRITE_GRAPH]"}, {"command-line-flag": "--dry-run", "description": "Do not run the workflow.", "id": "dry_run", "name": "dry_run", "optional": true, "type": "Flag", "default-value": false, "value-key": "[DRY_RUN]"}, {"command-line-flag": "--profile", "description": "hook up the resource profiler callback to nipype", "id": "profile", "name": "profile", "optional": true, "type": "Flag", "default-value": false, "value-key": "[PROFILE]"}, {"command-line-flag": "--use-plugin", "description": "Path to nipype plugin configuration file", "id": "use_plugin", "name": "use_plugin", "optional": true, "type": "String", "value-key": "[USE_PLUGIN]"}, {"command-line-flag": "--no-sub", "description": "Turn off submission of anonymized quality metrics to MRIQC's metrics repository.", "id": "no_sub", "name": "no_sub", "optional": true, "type": "Flag", "default-value": false, "value-key": "[NO_SUB]"}, {"command-line-flag": "--email", "description": "Email address to include with quality metric submission.", "id": "email", "name": "email", "optional": true, "type": "String", "value-key": "[EMAIL]"}, {"command-line-flag": "-v", "description": "increases log verbosity for each occurence, debug level is -vvv", "id": "verbose_count", "name": "verbose_count", "optional": true, "type": "String", "value-key": "[VERBOSE_COUNT]"}, {"command-line-flag": "--webapi-url", "default-value": "https://mriqc.nimh.nih.gov/api/v1", "description": "IP address where the MRIQC WebAPI is listening", "id": "webapi_url", "name": "webapi_url", "optional": true, "type": "String", "value-key": "[WEBAPI_URL]"}, {"command-line-flag": "--webapi-port", "description": "port where the MRIQC WebAPI is listening", "id": "webapi_port", "name": "webapi_port", "optional": true, "type": "Number", "value-key": "[WEBAPI_PORT]"}, {"command-line-flag": "--upload-strict", "description": "upload will fail if if upload is strict", "id": "upload_strict", "name": "upload_strict", "optional": true, "type": "Flag", "value-key": "[UPLOAD_STRICT]"}, {"command-line-flag": "--n_procs", "description": "number of threads", "id": "n_procs", "name": "n_procs", "optional": true, "type": "Number", "value-key": "[N_PROCS]"}, {"command-line-flag": "--mem_gb", "description": "available total memory", "id": "mem_gb", "name": "mem_gb", "optional": true, "type": "Number", "value-key": "[MEM_GB]"}, {"command-line-flag": "--testing", "description": "use testing settings for a minimal footprint", "id": "testing", "name": "testing", "optional": true, "type": "Flag", "value-key": "[TESTING]"}, {"command-line-flag": "-f", "description": "Cast the input data to float32 if it's represented in higher precision (saves space and improves perfomance)", "id": "float32", "name": "float32", "optional": true, "type": "Flag", "value-key": "[FLOAT32]"}, {"command-line-flag": "--ica", "description": "Run ICA on the raw data and include the componentsin the individual reports (slow but potentially very insightful)", "id": "ica", "name": "ica", "optional": true, "type": "Flag", "value-key": "[ICA]"}, {"command-line-flag": "--hmc-afni", "default-value": true, "description": "Use ANFI 3dvolreg for head motion correction (HMC) - default", "id": "hmc_afni", "name": "hmc_afni", "optional": true, "type": "Flag", "value-key": "[HMC_AFNI]"}, {"command-line-flag": "--hmc-fsl", "description": "Use FSL MCFLIRT instead of AFNI for head motion correction (HMC)", "id": "hmc_fsl", "name": "hmc_fsl", "optional": true, "type": "Flag", "value-key": "[HMC_FSL]"}, {"command-line-flag": "--fft-spikes-detector", "description": "Turn on FFT based spike detector (slow).", "id": "fft_spikes_detector", "name": "fft_spikes_detector", "optional": true, "type": "Flag", "value-key": "[FFT_SPIKES_DETECTOR]"}, {"command-line-flag": "--fd_thres", "default-value": 0.2, "description": "motion threshold for FD computation", "id": "fd_thres", "name": "fd_thres", "optional": true, "type": "Number", "value-key": "[FD_THRES]"}, {"command-line-flag": "--ants-nthreads", "default-value": 1, "description": "number of threads that will be set in ANTs processes", "id": "ants_nthreads", "name": "ants_nthreads", "optional": true, "type": "Number", "value-key": "[ANTS_NTHREADS]"}, {"command-line-flag": "--ants-float", "description": "use float number precision on ANTs computations", "id": "ants_float", "name": "ants_float", "optional": true, "type": "Flag", "value-key": "[ANTS_FLOAT]"}, {"command-line-flag": "--ants-settings", "description": "path to JSON file with settings for ANTS", "id": "ants_settings", "name": "ants_settings", "optional": true, "type": "String", "value-key": "[ANTS_SETTINGS]"}, {"command-line-flag": "--deoblique", "description": "Deoblique the functional scans during head motion correction preprocessing", "id": "deoblique", "name": "deoblique", "optional": true, "type": "Flag", "value-key": "[DEOBLIQUE]"}, {"command-line-flag": "--despike", "description": "Despike the functional scans during head motion correction preprocessing", "id": "despike", "name": "despike", "optional": true, "type": "Flag", "value-key": "[DESPIKE]"}, {"command-line-flag": "--start-idx", "description": "Initial volume in functional timeseries that should be considered for preprocessing", "id": "start_idx", "name": "start_idx", "optional": true, "type": "Number", "value-key": "[START_IDX]"}, {"command-line-flag": "--stop-idx", "description": "Final volume in functional timeseries that should be considered for preprocessing", "id": "stop_idx", "name": "stop_idx", "optional": true, "type": "Number", "value-key": "[STOP_IDX]"}, {"command-line-flag": "--correct-slice-timing", "description": "Perform slice timing correction", "id": "correct_slice_timing", "name": "correct_slice_timing", "optional": true, "type": "Flag", "value-key": "[CORRECT_SLICE_TIMING]"}], "outputfiles": [{"description": "This is the directory where the overall outputs are to be stored.", "id": "output_directory", "name": "Output Directory", "optional": false, "path-template": "[OUTPUT_DIR]"}], "groups": [{"name": "Instrumentation Options", "description": "Instrumental Options", "id": "instrument_options", "members": ["work_dir", "verbose_reports", "write_graph", "dry_run", "profile", "use_plugin", "no_sub", "email", "webapi_url", "webapi_port", "upload_strict"]}, {"name": "Performance Options", "description": "Options to handle performance", "id": "performance_options", "members": ["n_procs", "mem_gb", "testing", "float32"]}, {"name": "Workflow Options", "description": "Workflow options", "id": "workflow_options", "members": ["ica", "hmc_afni", "hmc_fsl", "fft_spikes_detector", "fd_thres"]}, {"name": "ANTs specific settings", "description": "ANTs specific settings", "id": "ants_specific_settings", "members": ["ants_settings", "ants_float", "ants_nthreads"]}, {"name": "AFNI specific settings", "description": "AFNI specific settings", "id": "afni_specific_settings", "members": ["deoblique", "despike", "start_idx", "stop_idx", "correct_slice_timing"]}], "name": "MRIQC", "suggestedresources": {"cpu-cores": 1, "ram": 4, "walltime-estimate": 172000}, "toolversion": "v0.14.2", "url": "https://mriqc.readthedocs.io/en/0.14.2", "ark_id": "https://n2t.net/ark:/70798/p78wmxc1g0nvx4m10b", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.1450995", "title": "PreFreeSurferPipelineBatch", "description": "PreFreeSurferPipelineBatch HCP pipeline", "publicationdate": "2018-10-08", "deprecated": false, "downloads": 3050, "author": "Washington University", "version": "3.19.0-centos7", "doi": "10.5281/zenodo.1450995", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "mri"]}, "toolversion": "3.19.0-centos7", "name": "PreFreeSurferPipelineBatch", "descriptorurl": "https://github.com/big-data-lab-team/cbrain-plugins-hcp/blob/master/cbrain_task_descriptors/prefreesurfer-exec-centos7-fslbuild-centos5.json", "commandline": "command-line-script.sh [SUBJECT_FOLDER] [NAME]", "inputs": [{"description": "HCP subject folder, downloaded from http://www.humanconnectome.org/documentation/S500.", "value-key": "[SUBJECT_FOLDER]", "type": "File", "optional": false, "id": "subject_folder", "name": "HCP subject folder"}, {"description": "Use this parameter to give a name to the execution. Example: \"Exec-CentOS5-FSLbuild-CentOS5\". The results will be written in a folder named [SUBJECT]-[EXECUTION-NAME] (a unique identifier will be appended in case a file with the same name already exists).", "default-value": "Exec-CentOS-[X]-FSLbuild-CentOS-[Y]", "value-key": "[NAME]", "optional": false, "type": "String", "id": "execution_name", "name": "Execution name"}], "containerimage": {"image": "bigdatalabteam/hcp-prefreesurfer:exec-centos7-fslbuild-centos5-latest", "type": "docker"}, "outputfiles": [{"path-template": "[SUBJECT_FOLDER]-[NAME]", "description": "This directory will contain 3 directories (T1w, T2w and MNINonLinear), a monitoring file (monitor.txt) and the input data.", "optional": false, "id": "results", "name": "Results"}], "suggestedresources": {"walltime-estimate": 25200}, "ark_id": "https://n2t.net/ark:/70798/p7xjtn7218dnw6qbg4", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2621482", "title": "TOPUP", "description": "TOPUP, as implemented in Nipype (module: nipype.interfaces.fsl, interface: TOPUP).", "publicationdate": "2019-04-02", "deprecated": false, "downloads": 3035, "author": "Nipype (interface), Oxford Centre for Functional MRI of the Brain (FMRIB) (tool)", "version": "1.0.0", "doi": "10.5281/zenodo.2621482", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "dmri"], "source": "nipype-interface"}, "name": "TOPUP", "commandline": "topup [CONFIG] [ENCODING_FILE] [ESTMOV] [FWHM] [IN_FILE] [INTERP] [MAX_ITER] [MINMET] [NUMPREC] [OUT_BASE] [OUT_CORRECTED] [OUT_FIELD] [OUT_JAC_PREFIX] [OUT_LOGFILE] [OUT_MAT_PREFIX] [OUT_WARP_PREFIX] [REG_LAMBDA] [REGMOD] [REGRID] [SCALE] [SPLINEORDER] [SSQLAMBDA] [SUBSAMP] [WARP_RES]", "inputs": [{"id": "config", "name": "Config", "type": "String", "value-key": "[CONFIG]", "command-line-flag": "--config", "command-line-flag-separator": "=", "description": "A string. Name of config file specifying command line arguments.", "optional": true, "default-value": "b02b0.cnf"}, {"id": "encoding_file", "name": "Encoding file", "type": "File", "value-key": "[ENCODING_FILE]", "command-line-flag": "--datain", "command-line-flag-separator": "=", "description": "An existing file name. Name of text file with pe directions/times.", "optional": false}, {"id": "estmov", "name": "Estmov", "type": "Number", "value-key": "[ESTMOV]", "command-line-flag": "--estmov", "command-line-flag-separator": "=", "description": "1 or 0. Estimate movements if set.", "optional": true, "integer": true, "value-choices": [1, 0]}, {"id": "fwhm", "name": "Fwhm", "type": "Number", "value-key": "[FWHM]", "command-line-flag": "--fwhm", "command-line-flag-separator": "=", "description": "A float. Fwhm (in mm) of gaussian smoothing kernel.", "optional": true}, {"id": "in_file", "name": "In file", "type": "File", "value-key": "[IN_FILE]", "command-line-flag": "--imain", "command-line-flag-separator": "=", "description": "An existing file name. Name of 4d file with images.", "optional": false}, {"id": "interp", "name": "Interp", "type": "String", "value-key": "[INTERP]", "command-line-flag": "--interp", "command-line-flag-separator": "=", "description": "'spline' or 'linear'. Image interpolation model, linear or spline.", "optional": true, "value-choices": ["spline", "linear"]}, {"id": "max_iter", "name": "Max iter", "type": "Number", "integer": true, "value-key": "[MAX_ITER]", "command-line-flag": "--miter", "command-line-flag-separator": "=", "description": "An integer (int or long). Max # of non-linear iterations.", "optional": true}, {"id": "minmet", "name": "Minmet", "type": "Number", "value-key": "[MINMET]", "command-line-flag": "--minmet", "command-line-flag-separator": "=", "description": "0 or 1. Minimisation method 0=levenberg-marquardt, 1=scaled conjugate gradient.", "optional": true, "integer": true, "value-choices": [0, 1]}, {"id": "numprec", "name": "Numprec", "type": "String", "value-key": "[NUMPREC]", "command-line-flag": "--numprec", "command-line-flag-separator": "=", "description": "'double' or 'float'. Precision for representing hessian, double or float.", "optional": true, "value-choices": ["double", "float"]}, {"id": "out_jac_prefix", "name": "Out jac prefix", "type": "String", "value-key": "[OUT_JAC_PREFIX]", "command-line-flag": "--jacout", "command-line-flag-separator": "=", "description": "A unicode string. Prefix for the warpfield images.", "optional": true, "default-value": "jac"}, {"id": "out_mat_prefix", "name": "Out mat prefix", "type": "String", "value-key": "[OUT_MAT_PREFIX]", "command-line-flag": "--rbmout", "command-line-flag-separator": "=", "description": "A unicode string. Prefix for the realignment matrices.", "optional": true, "default-value": "xfm"}, {"id": "out_warp_prefix", "name": "Out warp prefix", "type": "String", "value-key": "[OUT_WARP_PREFIX]", "command-line-flag": "--dfout", "command-line-flag-separator": "=", "description": "A unicode string. Prefix for the warpfield images (in mm).", "optional": true, "default-value": "warpfield"}, {"id": "reg_lambda", "name": "Reg lambda", "type": "Number", "value-key": "[REG_LAMBDA]", "command-line-flag": "--lambda", "command-line-flag-separator": "=", "description": "A float. Weight of regularisation, default depending on --ssqlambda and --regmod switches.", "optional": true}, {"id": "regmod", "name": "Regmod", "type": "String", "value-key": "[REGMOD]", "command-line-flag": "--regmod", "command-line-flag-separator": "=", "description": "'bending_energy' or 'membrane_energy'. Regularisation term implementation. defaults to bending_energy. note that the two functions have vastly different scales. the membrane energy is based on the first derivatives and the bending energy on the second derivatives. the second derivatives will typically be much smaller than the first derivatives, so input lambda will have to be larger for bending_energy to yield approximately the same level of regularisation.", "optional": true, "value-choices": ["bending_energy", "membrane_energy"]}, {"id": "regrid", "name": "Regrid", "type": "Number", "value-key": "[REGRID]", "command-line-flag": "--regrid", "command-line-flag-separator": "=", "description": "1 or 0. If set (=1), the calculations are done in a different grid.", "optional": true, "integer": true, "value-choices": [1, 0]}, {"id": "scale", "name": "Scale", "type": "Number", "value-key": "[SCALE]", "command-line-flag": "--scale", "command-line-flag-separator": "=", "description": "0 or 1. If set (=1), the images are individually scaled to a common mean.", "optional": true, "integer": true, "value-choices": [0, 1]}, {"id": "splineorder", "name": "Splineorder", "type": "Number", "integer": true, "value-key": "[SPLINEORDER]", "command-line-flag": "--splineorder", "command-line-flag-separator": "=", "description": "An integer (int or long). Order of spline, 2->qadratic spline, 3->cubic spline.", "optional": true}, {"id": "ssqlambda", "name": "Ssqlambda", "type": "Number", "value-key": "[SSQLAMBDA]", "command-line-flag": "--ssqlambda", "command-line-flag-separator": "=", "description": "1 or 0. Weight lambda by the current value of the ssd. if used (=1), the effective weight of regularisation term becomes higher for the initial iterations, therefore initial steps are a little smoother than they would without weighting. this reduces the risk of finding a local minimum.", "optional": true, "integer": true, "value-choices": [1, 0]}, {"id": "subsamp", "name": "Subsamp", "type": "Number", "integer": true, "value-key": "[SUBSAMP]", "command-line-flag": "--subsamp", "command-line-flag-separator": "=", "description": "An integer (int or long). Sub-sampling scheme.", "optional": true}, {"id": "warp_res", "name": "Warp res", "type": "Number", "value-key": "[WARP_RES]", "command-line-flag": "--warpres", "command-line-flag-separator": "=", "description": "A float. (approximate) resolution (in mm) of warp basis for the different sub-sampling levels.", "optional": true}], "outputfiles": [{"name": "Out base", "id": "out_base", "optional": true, "description": "A file name. Base-name of output files (spline coefficients (hz) and movement parameters).", "path-template": "[IN_FILE]_base", "path-template-stripped-extensions": [".nii.gz", ".nii"], "value-key": "[OUT_BASE]", "command-line-flag": "--out", "command-line-flag-separator": "="}, {"name": "Out corrected", "id": "out_corrected", "path-template": "[IN_FILE]_corrected", "path-template-stripped-extensions": [".nii.gz", ".nii"], "optional": true, "description": "A file name. Name of 4d image file with unwarped images.", "value-key": "[OUT_CORRECTED]", "command-line-flag": "--iout", "command-line-flag-separator": "="}, {"name": "Out enc file", "id": "out_enc_file", "path-template": "out_enc_file", "optional": true, "description": "A file name. Encoding directions file output for applytopup."}, {"name": "Out field", "id": "out_field", "path-template": "[IN_FILE]_field", "path-template-stripped-extensions": [".nii.gz", ".nii"], "optional": true, "description": "A file name. Name of image file with field (hz).", "value-key": "[OUT_FIELD]", "command-line-flag": "--fout", "command-line-flag-separator": "="}, {"name": "Out fieldcoef", "id": "out_fieldcoef", "path-template": "out_fieldcoef", "optional": true, "description": "An existing file name. File containing the field coefficients."}, {"name": "Out jacs", "id": "out_jacs", "path-template": "out_jacs", "optional": true, "description": "A list of items which are an existing file name. Jacobian images."}, {"name": "Out logfile", "id": "out_logfile", "path-template": "[IN_FILE]_topup.log", "path-template-stripped-extensions": [".nii.gz", ".nii"], "optional": true, "description": "A file name. Name of log-file.", "value-key": "[OUT_LOGFILE]", "command-line-flag": "--logout", "command-line-flag-separator": "="}, {"name": "Out mats", "id": "out_mats", "path-template": "out_mats", "optional": true, "description": "A list of items which are an existing file name. Realignment matrices."}, {"name": "Out movpar", "id": "out_movpar", "path-template": "out_movpar", "optional": true, "description": "An existing file name. Movpar.txt output file."}, {"name": "Out warps", "id": "out_warps", "path-template": "out_warps", "optional": true, "description": "A list of items which are an existing file name. Warpfield images."}], "toolversion": "1.0.0", "containerimage": {"image": "mcin/docker-fsl:latest", "type": "docker", "index": "index.docker.io"}, "url": "https://github.com/nipy/nipype/blob/master/nipype/interfaces/fsl/epi.py", "ark_id": "https://n2t.net/ark:/70798/p7hvkfsgx9xbj013rd", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2566443", "title": "mask2boundary", "description": "Transforms a binary mask of a niftii image (such as a brain or white matter mask) into a boundary mask. This tool was originally developed to transform a white matter mask into a mask of seed locations for performing tractography in diffusion images.", "publicationdate": "2019-02-15", "deprecated": false, "downloads": 3029, "author": "Greg Kiar", "version": "v0.1.0", "doi": "10.5281/zenodo.2566443", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "mri", "nifti", "dmri"]}, "commandline": "python3 /opt/mask2boundary.py [MASK] [OUTPUT] [WIDTH] [BOUTIQUES]", "containerimage": {"image": "gkiar/mask2boundary:v0.1.0", "index": "index.docker.io", "type": "docker"}, "inputs": [{"description": "Nifti image containing a binary mask.", "id": "mask", "name": "mask", "optional": false, "type": "String", "value-key": "[MASK]"}, {"description": "Path for output Nifti image containing the mask boundary.", "id": "output", "name": "output", "optional": false, "type": "String", "value-key": "[OUTPUT]"}, {"command-line-flag": "--width", "default-value": 3, "description": "Width of the boundary to be stored.", "id": "width", "integer": true, "minimum": 1, "name": "width", "optional": true, "type": "Number", "value-key": "[WIDTH]"}, {"command-line-flag": "--boutiques", "description": "Toggles creation of a Boutiques descriptor and invocation from the tool and inputs.", "id": "boutiques", "name": "boutiques", "optional": true, "type": "Flag", "value-key": "[BOUTIQUES]"}], "name": "mask2boundary", "outputfiles": [{"path-template": "[OUTPUT]", "optional": false, "id": "mask_boundary", "name": "Boundary Mask"}], "suggestedresources": {"cpu-cores": 1, "ram": 1, "walltime-estimate": 20}, "toolversion": "v0.1.0", "ark_id": "https://n2t.net/ark:/70798/p7jgxdzdq407f00k3w", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3267250", "title": "FslBet601", "description": "Automated brain extraction tool for FSL", "publicationdate": "2019-07-03", "deprecated": false, "downloads": 3026, "author": "Oxford Centre for Functional MRI of the Brain (FMRIB)", "version": "6.0.1", "doi": "10.5281/zenodo.3267250", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["neuroinformatics", "mri"]}, "toolversion": "6.0.1", "tests": [{"invocation": {"maskfile": "img_bet", "infile": "/validation-data/intro/structural.nii.gz"}, "name": "fsl_bet_test", "assertions": {"output-files": [{"id": "outfile", "md5-reference": "f31c5490041f1035cd06fd496d9e4efc"}], "exit-code": 0}}], "name": "FslBet601", "commandline": "bet [INPUT_FILE] [MASK] [FRACTIONAL_INTENSITY] [VERTICAL_GRADIENT] [CENTER_OF_GRAVITY] [OVERLAY_FLAG] [BINARY_MASK_FLAG] [APPROX_SKULL_FLAG] [NO_SEG_OUTPUT_FLAG] [VTK_VIEW_FLAG] [HEAD_RADIUS] [THRESHOLDING_FLAG] [ROBUST_ITERS_FLAG] [RES_OPTIC_CLEANUP_FLAG] [REDUCE_BIAS_FLAG] [SLICE_PADDING_FLAG] [MASK_WHOLE_SET_FLAG] [ADD_SURFACES_FLAG] [ADD_SURFACES_T2] [VERBOSE_FLAG] [DEBUG_FLAG]", "onlineplatformurls": ["https://portal.cbrain.mcgill.ca"], "containerimage": {"image": "shub://aces/cbrain-containers-recipes:fsl_v6.0.1", "type": "singularity"}, "descriptorurl": "https://github.com/aces/cbrain-plugins-neuro/blob/master/cbrain_task_descriptors/fsl_bet.json", "inputs": [{"description": "Input image (e.g. img.nii.gz)", "value-key": "[INPUT_FILE]", "type": "File", "optional": false, "id": "infile", "name": "Input file"}, {"description": "Output brain mask (e.g. img_bet.nii.gz)", "value-key": "[MASK]", "type": "String", "optional": false, "id": "maskfile", "name": "Mask file"}, {"command-line-flag": "-f", "description": "Fractional intensity threshold (0->1); default=0.5; smaller values give larger brain outline estimates", "value-key": "[FRACTIONAL_INTENSITY]", "optional": true, "maximum": 1, "minimum": 0, "integer": false, "type": "Number", "id": "fractional_intensity", "name": "Fractional intensity threshold"}, {"command-line-flag": "-g", "description": "Vertical gradient in fractional intensity threshold (-1->1); default=0; positive values give larger brain outline at bottom, smaller at top", "value-key": "[VERTICAL_GRADIENT]", "optional": true, "maximum": 1, "minimum": -1, "integer": false, "type": "Number", "id": "vg_fractional_intensity", "name": "Vertical gradient fractional intensity threshold"}, {"command-line-flag": "-c", "description": "The xyz coordinates of the center of gravity (voxels, not mm) of initial mesh surface. Must have exactly three numerical entries in the list (3-vector).", "value-key": "[CENTER_OF_GRAVITY]", "optional": true, "list": true, "max-list-entries": 3, "type": "Number", "id": "center_of_gravity", "min-list-entries": 3, "name": "Center of gravity vector"}, {"command-line-flag": "-o", "description": "Generate brain surface outline overlaid onto original image", "value-key": "[OVERLAY_FLAG]", "optional": true, "type": "Flag", "id": "overlay_flag", "name": "Overlay flag"}, {"command-line-flag": "-m", "description": "Generate binary brain mask", "value-key": "[BINARY_MASK_FLAG]", "optional": true, "type": "Flag", "id": "binary_mask_flag", "name": "Binary mask flag"}, {"command-line-flag": "-s", "description": "Generate rough skull image (not as clean as betsurf)", "value-key": "[APPROX_SKULL_FLAG]", "optional": true, "type": "Flag", "id": "approx_skull_flag", "name": "Approximate skull flag"}, {"command-line-flag": "-n", "description": "Don't generate segmented brain image output", "value-key": "[NO_SEG_OUTPUT_FLAG]", "optional": true, "type": "Flag", "id": "no_seg_output_flag", "name": "No segmented brain image flag"}, {"command-line-flag": "-e", "description": "Generate brain surface as mesh in .vtk format", "value-key": "[VTK_VIEW_FLAG]", "optional": true, "type": "Flag", "id": "vtk_mesh", "name": "VTK format brain surface mesh flag"}, {"command-line-flag": "-r", "description": "head radius (mm not voxels); initial surface sphere is set to half of this", "value-key": "[HEAD_RADIUS]", "optional": true, "type": "Number", "id": "head_radius", "name": "Head Radius"}, {"command-line-flag": "-t", "description": "Apply thresholding to segmented brain image and mask", "value-key": "[THRESHOLDING_FLAG]", "optional": true, "type": "Flag", "id": "thresholding_flag", "name": "Threshold segmented image flag"}, {"command-line-flag": "-R", "description": "More robust brain center estimation, by iterating BET with a changing center-of-gravity.", "value-key": "[ROBUST_ITERS_FLAG]", "optional": true, "type": "Flag", "id": "robust_iters_flag", "name": "Robust iterations flag"}, {"command-line-flag": "-S", "description": "This attempts to cleanup residual eye and optic nerve voxels which bet2 can sometimes leave behind. This can be useful when running SIENA or SIENAX, for example. Various stages involving standard-space masking, morphpological operations and thresholdings are combined to produce a result which can often give better results than just running bet2.", "value-key": "[RES_OPTIC_CLEANUP_FLAG]", "optional": true, "type": "Flag", "id": "residual_optic_cleanup_flag", "name": "Residual optic cleanup flag"}, {"command-line-flag": "-B", "description": "This attempts to reduce image bias, and residual neck voxels. This can be useful when running SIENA or SIENAX, for example. Various stages involving FAST segmentation-based bias field removal and standard-space masking are combined to produce a result which can often give better results than just running bet2.", "value-key": "[REDUCE_BIAS_FLAG]", "optional": true, "type": "Flag", "id": "reduce_bias_flag", "name": "Bias reduction flag"}, {"command-line-flag": "-Z", "description": "This can improve the brain extraction if only a few slices are present in the data (i.e., a small field of view in the Z direction). This is achieved by padding the end slices in both directions, copying the end slices several times, running bet2 and then removing the added slices.", "value-key": "[SLICE_PADDING_FLAG]", "optional": true, "type": "Flag", "id": "slice_padding_flag", "name": "Slice padding flag"}, {"command-line-flag": "-F", "description": "This option uses bet2 to determine a brain mask on the basis of the first volume in a 4D data set, and applies this to the whole data set. This is principally intended for use on FMRI data, for example to remove eyeballs. Because it is normally important (in this application) that masking be liberal (ie that there be little risk of cutting out valid brain voxels) the -f threshold is reduced to 0.3, and also the brain mask is \"dilated\" slightly before being used.", "value-key": "[MASK_WHOLE_SET_FLAG]", "optional": true, "type": "Flag", "id": "whole_set_mask_flag", "name": "Mask-whole-set flag"}, {"command-line-flag": "-A", "description": "This runs both bet2 and betsurf programs in order to get the additional skull and scalp surfaces created by betsurf. This involves registering to standard space in order to allow betsurf to find the standard space masks it needs.", "value-key": "[ADD_SURFACES_FLAG]", "optional": true, "type": "Flag", "id": "additional_surfaces_flag", "name": "Additional surfaces flag"}, {"command-line-flag": "-A2", "description": "This is the same as -A except that a T2 image is also input, to further improve the estimated skull and scalp surfaces. As well as carrying out the standard space registration this also registers the T2 to the T1 input image.", "value-key": "[ADD_SURFACES_T2]", "optional": true, "type": "File", "id": "additional_surfaces_t2", "name": "Additional surfaces with T2"}, {"command-line-flag": "-v", "description": "Switch on diagnostic messages", "value-key": "[VERBOSE_FLAG]", "optional": true, "type": "Flag", "id": "verbose_flag", "name": "Verbose Flag"}, {"command-line-flag": "-d", "description": "Don't delete temporary intermediate images", "value-key": "[DEBUG_FLAG]", "optional": true, "type": "Flag", "id": "debug_flag", "name": "Debug Flag"}], "groups": [{"name": "Main Program Parameters", "description": "Specify parameters that alter the default BET functionality", "members": ["fractional_intensity", "vg_fractional_intensity", "center_of_gravity", "overlay_flag", "binary_mask_flag", "approx_skull_flag", "no_seg_output_flag", "vtk_mesh", "head_radius", "thresholding_flag"], "id": "optional_params_group"}, {"name": "Variations on Default Functionality", "mutually-exclusive": true, "description": "Mutually exclusive options that specify variations on how BET should be run.", "members": ["robust_iters_flag", "residual_optic_cleanup_flag", "reduce_bias_flag", "slice_padding_flag", "whole_set_mask_flag", "additional_surfaces_flag", "additional_surfaces_t2"], "id": "variational_params_group"}, {"name": "Miscellaneous Parameters", "description": "Optional miscellaneous parameters when running BET", "members": ["verbose_flag", "debug_flag"], "id": "miscellaneous_params_group"}], "outputfiles": [{"id": "outfile", "optional": true, "path-template": "[MASK].nii.gz", "name": "Output mask file", "description": "Main default mask output of BET"}, {"id": "binary_mask", "optional": true, "path-template": "[MASK]_mask.nii.gz", "name": "Output binary mask file", "description": "Binary mask file (from -m option)"}, {"id": "overlay_file", "optional": true, "path-template": "[MASK]_overlay.nii.gz", "name": "Surface overlay file", "description": "Overlaid brain surface onto original image"}, {"id": "approx_skull_img", "optional": true, "path-template": "[MASK]_skull.nii.gz", "name": "Approximate skull file", "description": "Approximate skull image file"}, {"id": "output_vtk_mesh", "optional": true, "path-template": "[MASK]_mesh.vtk", "name": "VTK mesh", "description": "Mesh in VTK format"}, {"id": "skull_mask", "optional": true, "path-template": "[MASK]_skull_mask.nii.gz", "name": "Skull mask image", "description": "Output mask for skull image"}, {"id": "out_inskull_mask", "optional": true, "path-template": "[MASK]_inskull_mask.nii.gz", "name": "Output in-skull mask file", "description": "The in-skull mask file from betsurf (from -A or -A2)"}, {"id": "out_inskull_mesh", "optional": true, "path-template": "[MASK]_inskull_mesh.nii.gz", "name": "Output in-skull mesh file", "description": "The in-skull mesh file from betsurf (from -A or -A2)"}, {"id": "out_inskull_off", "optional": true, "path-template": "[MASK]_inskull_mesh.off", "name": "Output in-skull mesh off file", "description": "The in-skull mesh .off file from betsurf (from -A or -A2)"}, {"id": "out_outskin_mask", "optional": true, "path-template": "[MASK]_outskin_mask.nii.gz", "name": "Output out-skin mask file", "description": "The out-skin mask file from betsurf (from -A or -A2)"}, {"id": "out_outskin_mesh", "optional": true, "path-template": "[MASK]_outskin_mesh.nii.gz", "name": "Output out-skin mesh file", "description": "The out-skin mesh file from betsurf (from -A or -A2)"}, {"id": "out_outskin_off", "optional": true, "path-template": "[MASK]_outskin_mesh.off", "name": "Output out-skin mesh off file", "description": "The out-skin mesh .off file from betsurf (from -A or -A2)"}, {"id": "out_outskull_mask", "optional": true, "path-template": "[MASK]_outskull_mask.nii.gz", "name": "Output out-skull mask file", "description": "The out-skull mask file from betsurf (from -A or -A2)"}, {"id": "out_outskull_mesh", "optional": true, "path-template": "[MASK]_outskull_mesh.nii.gz", "name": "Output out-skull mesh file", "description": "The out-skull mesh file from betsurf (from -A or -A2)"}, {"id": "out_outskull_off", "optional": true, "path-template": "[MASK]_outskull_mesh.off", "name": "Output out-skull mesh off file", "description": "The out-skull mesh .off file from betsurf (from -A or -A2)"}], "suggestedresources": {"walltime-estimate": 28800, "nodes": 1, "ram": 4, "cpu-cores": 1}, "ark_id": "https://n2t.net/ark:/70798/p7k7wgvk93wpb6tc71", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2602072", "title": "BEDPOSTX5", "description": "BEDPOSTX5, as implemented in Nipype (module: nipype.interfaces.fsl, interface: BEDPOSTX5).", "publicationdate": "2019-03-21", "deprecated": false, "downloads": 3026, "author": "Nipype (interface), Oxford Centre for Functional MRI of the Brain (FMRIB) (tool)", "version": "1.0.0", "doi": "10.5281/zenodo.2602072", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "dmri"], "source": "nipype-interface"}, "name": "BEDPOSTX5", "commandline": "bedpostx [OUT_DIR] [ALL_ARD] [BURN_IN] [BURN_IN_NO_ARD] [BVALS] [BVECS] [CNLINEAR] [DWI] [F0_ARD] [F0_NOARD] [FORCE_DIR] [FUDGE] [GRAD_DEV] [GRADNONLIN] [LOGDIR] [MASK] [MODEL] [N_FIBRES] [N_JUMPS] [NO_ARD] [NO_SPAT] [NON_LINEAR] [RICIAN] [SAMPLE_EVERY] [SEED] [UPDATE_PROPOSAL_EVERY] [USE_GPU]", "inputs": [{"id": "all_ard", "name": "All ard", "type": "Flag", "value-key": "[ALL_ARD]", "command-line-flag": "--allard", "description": "A boolean. Turn ard on on all fibres.", "optional": true}, {"id": "burn_in", "name": "Burn in", "type": "Number", "minimum": 0, "value-key": "[BURN_IN]", "command-line-flag": "-b", "description": "A long integer >= 0. Total num of jumps at start of mcmc to be discarded.", "optional": true, "default-value": 0}, {"id": "burn_in_no_ard", "name": "Burn in no ard", "type": "Number", "minimum": 0, "value-key": "[BURN_IN_NO_ARD]", "command-line-flag": "--burnin_noard", "command-line-flag-separator": "=", "description": "A long integer >= 0. Num of burnin jumps before the ard is imposed.", "optional": true, "default-value": 0}, {"id": "bvals", "name": "Bvals", "type": "File", "value-key": "[BVALS]", "description": "An existing file name. B values file.", "optional": false}, {"id": "bvecs", "name": "Bvecs", "type": "File", "value-key": "[BVECS]", "description": "An existing file name. B vectors file.", "optional": false}, {"id": "cnlinear", "name": "Cnlinear", "type": "Flag", "value-key": "[CNLINEAR]", "command-line-flag": "--cnonlinear", "description": "A boolean. Initialise with constrained nonlinear fitting.", "optional": true}, {"id": "dwi", "name": "Dwi", "type": "File", "value-key": "[DWI]", "description": "An existing file name. Diffusion weighted image data file.", "optional": false}, {"id": "f0_ard", "name": "F0 ard", "type": "Flag", "value-key": "[F0_ARD]", "command-line-flag": "--f0 --ardf0", "description": "A boolean. Noise floor model: add to the model an unattenuated signal compartment f0.", "optional": true}, {"id": "f0_noard", "name": "F0 noard", "type": "Flag", "value-key": "[F0_NOARD]", "command-line-flag": "--f0", "description": "A boolean. Noise floor model: add to the model an unattenuated signal compartment f0.", "optional": true}, {"id": "force_dir", "name": "Force dir", "type": "Flag", "value-key": "[FORCE_DIR]", "command-line-flag": "--forcedir", "description": "A boolean. Use the actual directory name given (do not add + to make a new directory).", "optional": true, "default-value": true}, {"id": "fudge", "name": "Fudge", "type": "Number", "integer": true, "value-key": "[FUDGE]", "command-line-flag": "-w", "description": "An integer (int or long). Ard fudge factor.", "optional": true}, {"id": "grad_dev", "name": "Grad dev", "type": "File", "value-key": "[GRAD_DEV]", "description": "An existing file name. Grad_dev file, if gradnonlin, -g is true.", "optional": true}, {"id": "gradnonlin", "name": "Gradnonlin", "type": "Flag", "value-key": "[GRADNONLIN]", "command-line-flag": "-g", "description": "A boolean. Consider gradient nonlinearities, default off.", "optional": true}, {"id": "logdir", "name": "Logdir", "type": "File", "value-key": "[LOGDIR]", "command-line-flag": "--logdir", "command-line-flag-separator": "=", "description": "A directory name. No description provided.", "optional": true}, {"id": "mask", "name": "Mask", "type": "File", "value-key": "[MASK]", "description": "An existing file name. Bet binary mask file.", "optional": false}, {"id": "model", "name": "Model", "type": "Number", "value-key": "[MODEL]", "command-line-flag": "-model", "description": "1 or 2 or 3. Use monoexponential (1, default, required for single-shell) or multiexponential (2, multi-shell) model.", "optional": true, "integer": true, "value-choices": [1, 2, 3]}, {"id": "n_fibres", "name": "N fibres", "type": "Number", "minimum": 1, "value-key": "[N_FIBRES]", "command-line-flag": "-n", "description": "A long integer >= 1. Maximum number of fibres to fit in each voxel.", "optional": false, "default-value": 2}, {"id": "n_jumps", "name": "N jumps", "type": "Number", "integer": true, "value-key": "[N_JUMPS]", "command-line-flag": "-j", "description": "An integer (int or long). Num of jumps to be made by mcmc.", "optional": true, "default-value": 5000}, {"id": "no_ard", "name": "No ard", "type": "Flag", "value-key": "[NO_ARD]", "command-line-flag": "--noard", "description": "A boolean. Turn ard off on all fibres.", "optional": true}, {"id": "no_spat", "name": "No spat", "type": "Flag", "value-key": "[NO_SPAT]", "command-line-flag": "--nospat", "description": "A boolean. Initialise with tensor, not spatially.", "optional": true}, {"id": "non_linear", "name": "Non linear", "type": "Flag", "value-key": "[NON_LINEAR]", "command-line-flag": "--nonlinear", "description": "A boolean. Initialise with nonlinear fitting.", "optional": true}, {"id": "out_dir", "name": "Out dir", "type": "File", "value-key": "[OUT_DIR]", "description": "A directory name. Output directory.", "optional": false, "default-value": "bedpostx"}, {"id": "rician", "name": "Rician", "type": "Flag", "value-key": "[RICIAN]", "command-line-flag": "--rician", "description": "A boolean. Use rician noise modeling.", "optional": true}, {"id": "sample_every", "name": "Sample every", "type": "Number", "minimum": 0, "value-key": "[SAMPLE_EVERY]", "command-line-flag": "-s", "description": "A long integer >= 0. Num of jumps for each sample (mcmc).", "optional": true, "default-value": 1}, {"id": "seed", "name": "Seed", "type": "Number", "integer": true, "value-key": "[SEED]", "command-line-flag": "--seed", "command-line-flag-separator": "=", "description": "An integer (int or long). Seed for pseudo random number generator.", "optional": true}, {"id": "update_proposal_every", "name": "Update proposal every", "type": "Number", "minimum": 1, "value-key": "[UPDATE_PROPOSAL_EVERY]", "command-line-flag": "--updateproposalevery", "command-line-flag-separator": "=", "description": "A long integer >= 1. Num of jumps for each update to the proposal density std (mcmc).", "optional": true, "default-value": 40}, {"id": "use_gpu", "name": "Use gpu", "type": "Flag", "value-key": "[USE_GPU]", "command-line-flag": "--use_gpu", "description": "A boolean. Use the gpu version of bedpostx.", "optional": true}], "outputfiles": [{"name": "Dyads", "id": "dyads", "path-template": "dyads*", "optional": true, "description": "A list of items which are an existing file name. Mean of pdd distribution in vector form.", "list": true}, {"name": "Dyads dispersion", "id": "dyads_dispersion", "path-template": "dyads*_dispersion", "optional": true, "description": "A list of items which are an existing file name. Dispersion.", "list": true}, {"name": "Mean s0samples", "id": "mean_S0samples", "path-template": "mean_S0samples", "optional": true, "description": "An existing file name. Mean of distribution on t2wbaseline signal intensity s0."}, {"name": "Mean dsamples", "id": "mean_dsamples", "path-template": "mean_dsamples", "optional": true, "description": "An existing file name. Mean of distribution on diffusivity d."}, {"name": "Mean fsamples", "id": "mean_fsamples", "path-template": "mean_f*samples", "optional": true, "description": "A list of items which are an existing file name. Mean of distribution on f anisotropy.", "list": true}, {"name": "Mean phsamples", "id": "mean_phsamples", "path-template": "mean_ph*samples", "optional": true, "description": "A list of items which are an existing file name. Mean of distribution on phi.", "list": true}, {"name": "Mean thsamples", "id": "mean_thsamples", "path-template": "mean_th*samples", "optional": true, "description": "A list of items which are an existing file name. Mean of distribution on theta.", "list": true}, {"name": "Merged fsamples", "id": "merged_fsamples", "path-template": "merged_f*samples", "optional": true, "description": "A list of items which are an existing file name. Samples from the distribution on anisotropic volume fraction.", "list": true}, {"name": "Merged phsamples", "id": "merged_phsamples", "path-template": "merged_ph*samples", "optional": true, "description": "A list of items which are an existing file name. Samples from the distribution on phi.", "list": true}, {"name": "Merged thsamples", "id": "merged_thsamples", "path-template": "merged_th*samples", "optional": true, "description": "A list of items which are an existing file name. Samples from the distribution on theta.", "list": true}], "groups": [{"id": "mutex_group", "name": "Mutex group", "members": ["no_ard", "all_ard"], "mutually-exclusive": true}, {"id": "mutex_group_2", "name": "Mutex group 2", "members": ["non_linear", "no_spat", "cnlinear"], "mutually-exclusive": true}, {"id": "mutex_group_3", "name": "Mutex group 3", "members": ["f0_ard", "f0_noard"], "mutually-exclusive": true}, {"id": "mutex_group_4", "name": "Mutex group 4", "members": ["f0_ard", "f0_noard", "all_ard"], "mutually-exclusive": true}], "toolversion": "1.0.0", "containerimage": {"image": "mcin/docker-fsl:latest", "type": "docker", "index": "index.docker.io"}, "url": "https://github.com/nipy/nipype/blob/master/nipype/interfaces/fsl/dti.py", "ark_id": "https://n2t.net/ark:/70798/p7nrxkjmf3fg923n0h", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2621487", "title": "ApplyTOPUP", "description": "ApplyTOPUP, as implemented in Nipype (module: nipype.interfaces.fsl, interface: ApplyTOPUP).", "publicationdate": "2019-04-02", "deprecated": false, "downloads": 3020, "author": "Nipype (interface), Oxford Centre for Functional MRI of the Brain (FMRIB) (tool)", "version": "1.0.0", "doi": "10.5281/zenodo.2621487", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "dmri"], "source": "nipype-interface"}, "name": "ApplyTOPUP", "commandline": "applytopup [DATATYPE] [ENCODING_FILE] [IN_FILES] [IN_INDEX] [IN_TOPUP_FIELDCOEF] [INTERP] [METHOD] [OUT_CORRECTED]", "inputs": [{"id": "datatype", "name": "Datatype", "type": "String", "value-key": "[DATATYPE]", "command-line-flag": "--datatype", "command-line-flag-separator": "=", "description": "'char' or 'short' or 'int' or 'float' or 'double'. Force output data type.", "optional": true, "value-choices": ["char", "short", "int", "float", "double"]}, {"id": "encoding_file", "name": "Encoding file", "type": "File", "value-key": "[ENCODING_FILE]", "command-line-flag": "--datain", "command-line-flag-separator": "=", "description": "An existing file name. Name of text file with pe directions/times.", "optional": false}, {"id": "in_files", "name": "In files", "type": "File", "list": true, "list-separator": ",", "value-key": "[IN_FILES]", "command-line-flag": "--imain", "command-line-flag-separator": "=", "description": "A list of items which are an existing file name. Name of file with images.", "optional": false}, {"id": "in_index", "name": "In index", "type": "Number", "list": true, "integer": true, "list-separator": ",", "value-key": "[IN_INDEX]", "command-line-flag": "--inindex", "command-line-flag-separator": "=", "description": "A list of items which are an integer (int or long). Comma separated list of indices corresponding to --datain.", "optional": false}, {"id": "in_topup_fieldcoef", "name": "In topup fieldcoef", "type": "File", "value-key": "[IN_TOPUP_FIELDCOEF]", "command-line-flag": "--topup", "command-line-flag-separator": "=", "description": "An existing file name. Topup file containing the field coefficients.", "optional": false}, {"id": "interp", "name": "Interp", "type": "String", "value-key": "[INTERP]", "command-line-flag": "--interp", "command-line-flag-separator": "=", "description": "'trilinear' or 'spline'. Interpolation method.", "optional": true, "value-choices": ["trilinear", "spline"]}, {"id": "method", "name": "Method", "type": "String", "value-key": "[METHOD]", "command-line-flag": "--method", "command-line-flag-separator": "=", "description": "'jac' or 'lsr'. Use jacobian modulation (jac) or least-squares resampling (lsr).", "optional": true, "value-choices": ["jac", "lsr"]}], "outputfiles": [{"name": "Out corrected", "id": "out_corrected", "path-template": "out_corrected", "optional": false, "description": "An existing file name. Name of 4d image file with unwarped images.", "value-key": "[OUT_CORRECTED]", "command-line-flag": "--out", "command-line-flag-separator": "="}], "toolversion": "1.0.0", "containerimage": {"image": "mcin/docker-fsl:latest", "type": "docker", "index": "index.docker.io"}, "url": "https://github.com/nipy/nipype/blob/master/nipype/interfaces/fsl/epi.py", "ark_id": "https://n2t.net/ark:/70798/p7gp5x82k4zkw6wcj6", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2648761", "title": "CompositeTransformUtil", "description": "CompositeTransformUtil, as implemented in Nipype (module: nipype.interfaces.ants, interface: CompositeTransformUtil).", "publicationdate": "2019-04-22", "deprecated": false, "downloads": 3015, "author": "Nipype (interface), Brian B. Avants et al. (tool)", "version": "1.0.0", "doi": "10.5281/zenodo.2648761", "schemaversion": "0.5", "container": "docker", "tags": {"domain": "neuroinformatics", "source": "nipype-interface"}, "name": "CompositeTransformUtil", "commandline": "${ANTSPATH}/CompositeTransformUtil [PROCESS] [OUT_FILE] [IN_FILE] [OUTPUT_PREFIX]", "url": "https://github.com/nipy/nipype/blob/master/nipype/interfaces/ants/registration.py", "inputs": [{"id": "in_file", "name": "In file", "type": "File", "list": true, "value-key": "[IN_FILE]", "description": "A list of items which are an existing file name. Input transform file(s).", "optional": false}, {"id": "out_file", "name": "Out file", "type": "File", "value-key": "[OUT_FILE]", "description": "A file name. Output file path (only used for assembly).", "optional": true}, {"id": "output_prefix", "name": "Output prefix", "type": "String", "value-key": "[OUTPUT_PREFIX]", "description": "A unicode string. A prefix that is prepended to all output files (only used for disassembly).", "optional": true, "default-value": "transform"}, {"id": "process", "name": "Process", "type": "String", "value-key": "[PROCESS]", "command-line-flag": "--", "command-line-flag-separator": "", "description": "'assemble' or 'disassemble'. What to do with the transform inputs (assemble or disassemble).", "optional": true, "default-value": "assemble", "value-choices": ["assemble", "disassemble"], "value-disables": {"assemble": ["output_prefix"], "disassemble": ["out_file"]}}], "outputfiles": [{"name": "Affine transform", "id": "affine_transform", "path-template": "00_[OUTPUT_PREFIX]_AffineTransform.mat", "optional": true, "description": "A file name. Affine transform component."}, {"name": "Displacement field", "id": "displacement_field", "path-template": "01_[OUTPUT_PREFIX]_DisplacementFieldTransform.nii.gz", "optional": true, "description": "A file name. Displacement field component."}, {"name": "Out file", "id": "out_file_outfile", "path-template": "[OUT_FILE]", "optional": true, "description": "A file name. Compound transformation file."}], "toolversion": "1.0.0", "containerimage": {"image": "bt5e/ants:latest", "index": "index.docker.io", "type": "docker"}, "ark_id": "https://n2t.net/ark:/70798/p72cndgkq6j061c70v", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2646555", "title": "LaplacianThickness", "description": "LaplacianThickness, as implemented in Nipype (module: nipype.interfaces.ants, interface: LaplacianThickness).", "publicationdate": "2019-04-18", "deprecated": false, "downloads": 3015, "author": "Nipype (interface), Brian B. Avants et al. (tool)", "version": "1.0.0", "doi": "10.5281/zenodo.2646555", "schemaversion": "0.5", "container": "docker", "tags": {"domain": "neuroinformatics", "source": "nipype-interface"}, "name": "LaplacianThickness", "commandline": "${ANTSPATH}/LaplacianThickness [INPUT_WM] [INPUT_GM] [OUTPUT_IMAGE] [SMOOTH_PARAM] [PRIOR_THICKNESS] [DT] [SULCUS_PRIOR] [TOLERANCE]", "inputs": [{"id": "dT", "name": "Dt", "type": "Number", "value-key": "[DT]", "description": "A float. Time delta used during integration (defaults to 0.01).", "optional": true, "requires-inputs": ["prior_thickness"]}, {"id": "input_gm", "name": "Input gm", "type": "File", "value-key": "[INPUT_GM]", "description": "A file name. Gray matter segmentation image.", "optional": false}, {"id": "input_wm", "name": "Input wm", "type": "File", "value-key": "[INPUT_WM]", "description": "A file name. White matter segmentation image.", "optional": false}, {"id": "prior_thickness", "name": "Prior thickness", "type": "Number", "value-key": "[PRIOR_THICKNESS]", "description": "A float. Prior thickness (defaults to 500).", "optional": true, "requires-inputs": ["smooth_param"]}, {"id": "smooth_param", "name": "Smooth param", "type": "Number", "value-key": "[SMOOTH_PARAM]", "description": "A float. Sigma of the laplacian recursive image filter (defaults to 1).", "optional": true}, {"id": "sulcus_prior", "name": "Sulcus prior", "type": "Number", "value-key": "[SULCUS_PRIOR]", "description": "A float. Positive floating point number for sulcus prior. Authors said that 0.15 might be a reasonable value.", "optional": true, "requires-inputs": ["dT"]}, {"id": "tolerance", "name": "Tolerance", "type": "Number", "value-key": "[TOLERANCE]", "description": "A float. Tolerance to reach during optimization (defaults to 0.001).", "optional": true, "requires-inputs": ["sulcus_prior"]}], "outputfiles": [{"name": "Output image", "id": "output_image", "optional": true, "description": "An existing file name. Cortical thickness.", "path-template": "[INPUT_WM]_thickness", "value-key": "[OUTPUT_IMAGE]"}], "toolversion": "1.0.0", "containerimage": {"image": "bt5e/ants:latest", "index": "index.docker.io", "type": "docker"}, "ark_id": "https://n2t.net/ark:/70798/p7hbqzh4p7xbj4qmpv", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2634608", "title": "CorticalThickness", "description": "CorticalThickness, as implemented in Nipype (module: nipype.interfaces.ants, interface: CorticalThickness).", "publicationdate": "2019-04-10", "deprecated": false, "downloads": 3006, "author": "Nipype (interface), Brian B. Avants et al. (tool)", "version": "1.0.0", "doi": "10.5281/zenodo.2634608", "schemaversion": "0.5", "container": "docker", "tags": {"source": "nipype-interface", "domain": "neuroinformatics"}, "inputs": [{"command-line-flag": "-a", "description": "An existing file name. Structural *intensity* image, typically t1. if more than one anatomical image is specified, subsequently specified images are used during the segmentation process. however, only the first image is used in the registration of priors. our suggestion would be to specify the t1 as the first image.", "value-key": "[ANATOMICAL_IMAGE]", "optional": false, "type": "File", "id": "anatomical_image", "name": "Anatomical image"}, {"command-line-flag": "-v", "description": "A boolean. Use b-spline syn for registrations and b-spline exponential mapping in direct.", "value-key": "[B_SPLINE_SMOOTHING]", "optional": true, "type": "Flag", "id": "b_spline_smoothing", "name": "B spline smoothing"}, {"command-line-flag": "-m", "description": "An existing file name. Brain probability mask in template space.", "value-key": "[BRAIN_PROBABILITY_MASK]", "optional": false, "type": "File", "id": "brain_probability_mask", "name": "Brain probability mask"}, {"command-line-flag": "-e", "description": "An existing file name. Anatomical *intensity* template (possibly created using a population data set with buildtemplateparallel.sh in ants). this template is  *not* skull-stripped.", "value-key": "[BRAIN_TEMPLATE]", "optional": false, "type": "File", "id": "brain_template", "name": "Brain template"}, {"command-line-flag": "-r", "description": "An existing file name. Cortical roi labels to use as a prior for atith.", "value-key": "[CORTICAL_LABEL_IMAGE]", "optional": true, "type": "File", "id": "cortical_label_image", "name": "Cortical label image"}, {"command-line-flag": "-z 1", "description": "A boolean. If > 0, runs a faster version of the script. only for testing. implies -u 0. requires single thread computation for complete reproducibility.", "value-key": "[DEBUG]", "optional": true, "type": "Flag", "id": "debug", "name": "Debug"}, {"command-line-flag": "-d", "description": "3 or 2. Image dimension (2 or 3).", "default-value": 3, "value-key": "[DIMENSION]", "optional": true, "value-choices": [3, 2], "integer": true, "type": "Number", "id": "dimension", "name": "Dimension"}, {"command-line-flag": "-f", "description": "An existing file name. Mask (defined in the template space) used during registration for brain extraction.", "value-key": "[EXTRACTION_REGISTRATION_MASK]", "optional": true, "type": "File", "id": "extraction_registration_mask", "name": "Extraction registration mask"}, {"command-line-flag": "-s", "description": "A unicode string. Any of standard itk formats, nii.gz is default.", "default-value": "nii.gz", "value-key": "[IMAGE_SUFFIX]", "optional": true, "type": "String", "id": "image_suffix", "name": "Image suffix"}, {"command-line-flag": "-k", "name": "Keep temporary files", "value-key": "[KEEP_TEMPORARY_FILES]", "optional": true, "integer": true, "type": "Number", "id": "keep_temporary_files", "description": "An integer (int or long). Keep brain extraction/segmentation warps, etc (default = 0)."}, {"command-line-flag": "-l", "description": "A unicode string. Incorporate a distance prior one the posterior formulation.  should be of the form 'label[lambda,boundaryprobability]' where label is a value of 1,2,3,... denoting label id.  the label probability for anything outside the current label = boundaryprobability * exp( -lambda * distancefromboundary ) intuitively, smaller lambda values will increase the spatial capture range of the distance prior.  to apply to all label values, simply omit specifying the label, i.e. -l [lambda,boundaryprobability].", "value-key": "[LABEL_PROPAGATION]", "optional": true, "type": "String", "id": "label_propagation", "name": "Label propagation"}, {"command-line-flag": "-i", "name": "Max iterations", "value-key": "[MAX_ITERATIONS]", "optional": true, "integer": true, "type": "Number", "id": "max_iterations", "description": "An integer (int or long). Ants registration max iterations (default = 100x100x70x20)."}, {"description": "An integer (int or long). Number of itk threads to use.", "default-value": 1, "value-key": "[NUM_THREADS]", "optional": true, "integer": true, "type": "Number", "id": "num_threads", "name": "Num threads"}, {"command-line-flag": "-o", "description": "A unicode string. Prefix that is prepended to all output files (default = antsct_).", "default-value": "antsCT_", "value-key": "[OUT_PREFIX]", "optional": true, "type": "String", "id": "out_prefix", "name": "Out prefix"}, {"command-line-flag": "-b", "description": "A unicode string. Atropos posterior formulation and whether or not to use mixture model proportions. e.g 'socrates[1]' (default) or 'aristotle[1]'. choose the latter if you want use the distance priors (see also the -l option for label propagation control).", "value-key": "[POSTERIOR_FORMULATION]", "optional": true, "type": "String", "id": "posterior_formulation", "name": "Posterior formulation"}, {"command-line-flag": "-w", "description": "A float. Atropos spatial prior *probability* weight for the segmentation.", "value-key": "[PRIOR_SEGMENTATION_WEIGHT]", "optional": true, "type": "Number", "id": "prior_segmentation_weight", "name": "Prior segmentation weight"}, {"command-line-flag": "-q 1", "description": "A boolean. If = 1, use antsregistrationsynquick.sh as the basis for registration during brain extraction, brain segmentation, and (optional) normalization to a template. otherwise use antsregistrationsyn.sh (default = 0).", "value-key": "[QUICK_REGISTRATION]", "optional": true, "type": "Flag", "id": "quick_registration", "name": "Quick registration"}, {"command-line-flag": "-n", "name": "Segmentation iterations", "value-key": "[SEGMENTATION_ITERATIONS]", "optional": true, "integer": true, "type": "Number", "id": "segmentation_iterations", "description": "An integer (int or long). N4 -> atropos -> n4 iterations during segmentation (default = 3)."}, {"command-line-flag": "-p", "name": "Segmentation priors", "value-key": "[SEGMENTATION_PRIORS]", "optional": false, "list": true, "type": "File", "id": "segmentation_priors", "description": "A list of items which are an existing file name. No description provided."}, {"command-line-flag": "-t", "description": "An existing file name. Anatomical *intensity* template (assumed to be skull-stripped). a common case would be where this would be the same template as specified in the -e option which is not skull stripped.", "value-key": "[T1_REGISTRATION_TEMPLATE]", "optional": false, "type": "File", "id": "t1_registration_template", "name": "T1 registration template"}, {"command-line-flag": "-j", "description": "0 or 1. Use floating point precision in registrations (default = 0).", "value-key": "[USE_FLOATINGPOINT_PRECISION]", "optional": true, "value-choices": [0, 1], "integer": true, "type": "Number", "id": "use_floatingpoint_precision", "name": "Use floatingpoint precision"}, {"command-line-flag": "-u", "description": "0 or 1. Use random number generated from system clock in atropos (default = 1).", "value-key": "[USE_RANDOM_SEEDING]", "optional": true, "value-choices": [0, 1], "integer": true, "type": "Number", "id": "use_random_seeding", "name": "Use random seeding"}], "commandline": "${ANTSPATH}/antsCorticalThickness.sh [ANATOMICAL_IMAGE] [B_SPLINE_SMOOTHING] [BRAIN_PROBABILITY_MASK] [BRAIN_TEMPLATE] [CORTICAL_LABEL_IMAGE] [DEBUG] [DIMENSION] [EXTRACTION_REGISTRATION_MASK] [IMAGE_SUFFIX] [KEEP_TEMPORARY_FILES] [LABEL_PROPAGATION] [MAX_ITERATIONS] [NUM_THREADS] [OUT_PREFIX] [POSTERIOR_FORMULATION] [PRIOR_SEGMENTATION_WEIGHT] [QUICK_REGISTRATION] [SEGMENTATION_ITERATIONS] [SEGMENTATION_PRIORS] [T1_REGISTRATION_TEMPLATE] [USE_FLOATINGPOINT_PRECISION] [USE_RANDOM_SEEDING]", "url": "https://github.com/nipy/nipype/blob/master/nipype/interfaces/ants/segmentation.py", "toolversion": "1.0.0", "containerimage": {"index": "index.docker.io", "image": "bt5e/ants:latest", "type": "docker"}, "outputfiles": [{"path-template": "[OUT_PREFIX]BrainExtractionMask.[IMAGE_SUFFIX]", "description": "An existing file name. Brain extraction mask.", "optional": true, "name": "Brainextractionmask", "id": "BrainExtractionMask"}, {"path-template": "[OUT_PREFIX]BrainSegmentation.[IMAGE_SUFFIX]", "description": "An existing file name. Brain segmentaion image.", "optional": true, "name": "Brainsegmentation", "id": "BrainSegmentation"}, {"path-template": "[OUT_PREFIX]BrainSegmentation*N4.[IMAGE_SUFFIX]", "description": "An existing file name. N4 corrected image.", "optional": true, "name": "Brainsegmentationn4", "id": "BrainSegmentationN4"}, {"description": "A list of items which are an existing file name. Posterior probability images.", "list": true, "id": "BrainSegmentationPosteriors", "optional": true, "path-template": "[OUT_PREFIX]BrainSegmentationPosteriors*.[IMAGE_SUFFIX]", "name": "Brainsegmentationposteriors"}, {"path-template": "[OUT_PREFIX]brainvols.csv", "description": "An existing file name. Brain volumes as text.", "optional": true, "name": "Brainvolumes", "id": "BrainVolumes"}, {"path-template": "[OUT_PREFIX]CorticalThickness.[IMAGE_SUFFIX]", "description": "An existing file name. Cortical thickness file.", "optional": true, "name": "Corticalthickness", "id": "CorticalThickness"}, {"path-template": "[OUT_PREFIX]NormalizedCorticalThickness.[IMAGE_SUFFIX]", "description": "An existing file name. Normalized cortical thickness.", "optional": true, "name": "Corticalthicknessnormedtotemplate", "id": "CorticalThicknessNormedToTemplate"}, {"path-template": "[OUT_PREFIX]ExtractedBrain0N4.[IMAGE_SUFFIX]", "description": "An existing file name. Extracted brain from n4 image.", "optional": true, "name": "Extractedbrainn4", "id": "ExtractedBrainN4"}, {"path-template": "[OUT_PREFIX]SubjectToTemplate0GenericAffine.mat", "description": "An existing file name. Template to subject inverse affine.", "optional": true, "name": "Subjecttotemplate0genericaffine", "id": "SubjectToTemplate0GenericAffine"}, {"path-template": "[OUT_PREFIX]SubjectToTemplate1Warp.[IMAGE_SUFFIX]", "description": "An existing file name. Template to subject inverse warp.", "optional": true, "name": "Subjecttotemplate1warp", "id": "SubjectToTemplate1Warp"}, {"path-template": "[OUT_PREFIX]SubjectToTemplateLogJacobian.[IMAGE_SUFFIX]", "description": "An existing file name. Template to subject log jacobian.", "optional": true, "name": "Subjecttotemplatelogjacobian", "id": "SubjectToTemplateLogJacobian"}, {"path-template": "[OUT_PREFIX]TemplateToSubject0Warp.[IMAGE_SUFFIX]", "description": "An existing file name. Template to subject warp.", "optional": true, "name": "Templatetosubject0warp", "id": "TemplateToSubject0Warp"}, {"path-template": "[OUT_PREFIX]TemplateToSubject1GenericAffine.mat", "description": "An existing file name. Template to subject affine.", "optional": true, "name": "Templatetosubject1genericaffine", "id": "TemplateToSubject1GenericAffine"}], "name": "CorticalThickness", "ark_id": "https://n2t.net/ark:/70798/p7zjh18cg82mt4pxbx", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2640953", "title": "ConcatTransfo", "description": "Concatenate multiple ANTs warping fields using ComposeMultiTransform.\n\nFor instance if you have\n- Warping field: anatomical to MNI template\n- Affine matrix: Diffusion to anatomical\nYou can obtain the transform diffusion to MNI template\n\n\nComposeMultiTransform ImageDimension output_field [-R reference_image] {[deformation_field | [-i] affine_transform_txt ]}\n  Usage has the same form as WarpImageMultiTransform\n For Example:\n\nComposeMultiTransform Dimension  outwarp.nii   -R template.nii   ExistingWarp.nii  ExistingAffine.nii\n or for an inverse mapping :\nComposeMultiTransform Dimension  outwarp.nii   -R template.nii   -i ExistingAffine.nii ExistingInverseWarp.nii\n recalling that the -i option takes the inverse of the affine mapping\n\nOr: to compose multiple affine text file into one:\nComposeMultiTransform ImageDimension output_affine_txt [-R reference_affine_txt] {[-i] affine_transform_txt}\nThis will be evoked if a text file is given as the second parameter. In this case reference_affine_txt is used to define the center of the output affine.  The default reference is the first given affine text file. This ignores all non-txt files among the following parameters.\n\n", "publicationdate": "2019-04-15", "deprecated": false, "downloads": 3004, "author": "TONIC", "version": "1.0.0", "doi": "10.5281/zenodo.2640953", "schemaversion": "0.5", "container": "docker", "tags": "Boutiques", "toolversion": "1.0.0", "commandline": "ComposeMultiTransform 3 [OUPUT_WARPING_FIELD] -R [REFERENCE_IMAGE] [1ST_WARPING_FIELD__OR_AFFINE_MATRIX_] [2ND_WARPING_FIELD]", "containerimage": {"image": "bids/mrtrix3_connectome", "type": "docker"}, "inputs": [{"description": "Reference Image", "value-key": "[REFERENCE_IMAGE]", "type": "File", "optional": false, "id": "reference_image", "name": "Reference Image"}, {"description": "1st warping field (or affine matrix)", "value-key": "[1ST_WARPING_FIELD__OR_AFFINE_MATRIX_]", "type": "File", "optional": false, "id": "1st_warping_field__or_affine_matrix_", "name": "1st warping field (or affine matrix)"}, {"description": "2nd warping field", "value-key": "[2ND_WARPING_FIELD]", "type": "File", "optional": false, "id": "2nd_warping_field", "name": "2nd warping field"}], "outputfiles": [{"description": "Ouput warping field", "value-key": "[OUPUT_WARPING_FIELD]", "path-template": "./", "optional": false, "id": "ouput_warping_field", "name": "Ouput warping field"}], "name": "ConcatTransfo", "ark_id": "https://n2t.net/ark:/70798/p7f4xvdvd8gr80n0c0", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2650465", "title": "DistanceMap", "description": "DistanceMap, as implemented in Nipype (module: nipype.interfaces.fsl, interface: DistanceMap).", "publicationdate": "2019-04-24", "deprecated": false, "downloads": 3003, "author": "Nipype (interface), Oxford Centre for Functional MRI of the Brain (FMRIB) (tool)", "version": "1.0.0", "doi": "10.5281/zenodo.2650465", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "mri"], "source": "nipype-interface"}, "name": "DistanceMap", "commandline": "distancemap  [DISTANCE_MAP] [IN_FILE] [INVERT_INPUT] [LOCAL_MAX_FILE] [MASK_FILE]", "url": "https://github.com/nipy/nipype/blob/master/nipype/interfaces/fsl/dti.py", "inputs": [{"id": "distance_map", "name": "Distance map", "type": "File", "value-key": "[DISTANCE_MAP]", "command-line-flag": "--out", "command-line-flag-separator": "=", "description": "A file name. Distance map to write.", "optional": false}, {"id": "in_file", "name": "In file", "type": "File", "value-key": "[IN_FILE]", "command-line-flag": "--in", "command-line-flag-separator": "=", "description": "An existing file name. Image to calculate distance values for.", "optional": false}, {"id": "invert_input", "name": "Invert input", "type": "Flag", "value-key": "[INVERT_INPUT]", "command-line-flag": "--invert", "description": "A boolean. Invert input image.", "optional": true}, {"id": "local_max_file", "name": "Local max file", "type": "File", "value-key": "[LOCAL_MAX_FILE]", "command-line-flag": "--localmax", "command-line-flag-separator": "=", "description": "An existing file name. Write an image of the local maxima.", "optional": true}, {"id": "mask_file", "name": "Mask file", "type": "File", "value-key": "[MASK_FILE]", "command-line-flag": "--mask", "command-line-flag-separator": "=", "description": "An existing file name. Binary mask to contrain calculations.", "optional": true}], "outputfiles": [{"name": "Distance map", "id": "distance_map_outfile", "path-template": "[DISTANCE_MAP]", "optional": true, "description": "An existing file name. Value is distance to nearest nonzero voxels."}, {"name": "Local max file", "id": "local_max_file_outfile", "path-template": "[LOCAL_MAX_FILE]", "optional": true, "description": "A file name. Image of local maxima."}], "toolversion": "1.0.0", "containerimage": {"image": "mcin/docker-fsl:latest", "type": "docker", "index": "index.docker.io"}, "ark_id": "https://n2t.net/ark:/70798/p772fdm5f0bpq649g9", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.2650440", "title": "ApplyWarp", "description": "ApplyWarp, as implemented in Nipype (module: nipype.interfaces.fsl, interface: ApplyWarp).", "publicationdate": "2019-04-24", "deprecated": false, "downloads": 3002, "author": "Nipype (interface), Oxford Centre for Functional MRI of the Brain (FMRIB) (tool)", "version": "1.0.0", "doi": "10.5281/zenodo.2650440", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "mri"], "source": "nipype-interface"}, "name": "ApplyWarp", "commandline": "applywarp [INTERP] [IN_FILE] [REF_FILE] [OUT_FILE] [RELWARP] [ABSWARP] [DATATYPE] [FIELD_FILE] [MASK_FILE] [POSTMAT] [PREMAT] [SUPERLEVEL] [SUPERSAMPLE]", "url": "https://github.com/nipy/nipype/blob/master/nipype/interfaces/fsl/preprocess.py", "inputs": [{"id": "abswarp", "name": "Abswarp", "type": "Flag", "value-key": "[ABSWARP]", "command-line-flag": "--abs", "description": "A boolean. Treat warp field as absolute: x' = w(x).", "optional": true}, {"id": "datatype", "name": "Datatype", "type": "String", "value-key": "[DATATYPE]", "command-line-flag": "--datatype", "command-line-flag-separator": "=", "description": "'char' or 'short' or 'int' or 'float' or 'double'. Force output data type [char short int float double].", "optional": true, "value-choices": ["char", "short", "int", "float", "double"]}, {"id": "field_file", "name": "Field file", "type": "File", "value-key": "[FIELD_FILE]", "command-line-flag": "--warp", "command-line-flag-separator": "=", "description": "An existing file name. File containing warp field.", "optional": true}, {"id": "in_file", "name": "In file", "type": "File", "value-key": "[IN_FILE]", "command-line-flag": "--in", "command-line-flag-separator": "=", "description": "An existing file name. Image to be warped.", "optional": false}, {"id": "interp", "name": "Interp", "type": "String", "value-key": "[INTERP]", "command-line-flag": "--interp", "command-line-flag-separator": "=", "description": "'nn' or 'trilinear' or 'sinc' or 'spline'. Interpolation method.", "optional": true, "value-choices": ["nn", "trilinear", "sinc", "spline"]}, {"id": "mask_file", "name": "Mask file", "type": "File", "value-key": "[MASK_FILE]", "command-line-flag": "--mask", "command-line-flag-separator": "=", "description": "An existing file name. Filename for mask image (in reference space).", "optional": true}, {"id": "out_file", "name": "Out file", "type": "File", "value-key": "[OUT_FILE]", "command-line-flag": "--out", "command-line-flag-separator": "=", "description": "A file name. Output filename.", "optional": false}, {"id": "postmat", "name": "Postmat", "type": "File", "value-key": "[POSTMAT]", "command-line-flag": "--postmat", "command-line-flag-separator": "=", "description": "An existing file name. Filename for post-transform (affine matrix).", "optional": true}, {"id": "premat", "name": "Premat", "type": "File", "value-key": "[PREMAT]", "command-line-flag": "--premat", "command-line-flag-separator": "=", "description": "An existing file name. Filename for pre-transform (affine matrix).", "optional": true}, {"id": "ref_file", "name": "Ref file", "type": "File", "value-key": "[REF_FILE]", "command-line-flag": "--ref", "command-line-flag-separator": "=", "description": "An existing file name. Reference image.", "optional": false}, {"id": "relwarp", "name": "Relwarp", "type": "Flag", "value-key": "[RELWARP]", "command-line-flag": "--rel", "description": "A boolean. Treat warp field as relative: x' = x + w(x).", "optional": true}, {"id": "superlevel", "name": "Superlevel", "type": "String", "value-key": "[SUPERLEVEL]", "command-line-flag": "--superlevel", "command-line-flag-separator": "=", "description": "'a' or an integer (int or long). Level of intermediary supersampling, a for 'automatic' or integer level. default = 2.", "optional": true, "value-choices": ["a"]}, {"id": "superlevel_int", "name": "Superlevel", "type": "Number", "integer": true, "value-key": "[SUPERLEVEL]", "command-line-flag": "--superlevel", "command-line-flag-separator": "=", "description": "'a' or an integer (int or long). Level of intermediary supersampling, a for 'automatic' or integer level. default = 2.", "optional": true}, {"id": "supersample", "name": "Supersample", "type": "Flag", "value-key": "[SUPERSAMPLE]", "command-line-flag": "--super", "description": "A boolean. Intermediary supersampling of output, default is off.", "optional": true}], "outputfiles": [{"name": "Out file", "id": "out_file_outfile", "path-template": "[OUT_FILE]", "optional": true, "description": "An existing file name. 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in pixels)", "value-key": "[IMAGESIZE]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "imageSize"}, {"command-line-flag": "", "name": "2D coordinates of the circle center (in pixels; e.g., 200 250)", "value-key": "[CIRCLECENTER]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "circleCenter"}, {"command-line-flag": "", "name": "Output directory name", "value-key": "[DIROUT]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "dirOut"}, {"command-line-flag": "", "name": "Use noise='gaussian' (addition of gaussian noise) or noise='poisson' (generation of Poisson noise).", "value-key": "[NOISETYPE]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "noiseType"}, {"command-line-flag": "", "name": "If 'gaussian' (additive noise), please specify the Peak-to-peak Signe-to-noise ratio (PPSNR, in dB). If 'poisson', please specify a scaling factor ranging in [0:1].", "value-key": "[NOISEAMOUNT]", "optional": false, "type": "String", "id": "noiseAmount"}], "outputfiles": [{"description": "archive of the output folder containing execution results, and the output of the command", "value-key": "[RESULTS]", "id": "resultTarball", "optional": false, "path-template": "results.tar.gz", "name": "resultTarball"}], "ark_id": "https://n2t.net/ark:/70798/p7xq71x336psj2dvhv", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3240577", "title": "blastn", "description": "Nucleotide-Nucleotide BLAST 2.7.1+", "publicationdate": "2019-06-06", "deprecated": false, "downloads": 2982, "author": "Altschul et al.", "version": "v2.7.1", "doi": "10.5281/zenodo.3240577", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["bioinformatics", "blast"]}, "toolversion": "v2.7.1", "tests": [{"invocation": {"query": "test1_query.fasta", "outfmt": "5", "db": "sample", "max_target_seqs": 5, "out": "blastn.out"}, "name": "test1", "assertions": {"output-files": [{"id": "output", "md5-reference": "eb917a2e0723ee9cca9d86db85e83b69"}], "exit-code": 0}}], "commandline": "init_genpipes -a /tmp/$USER/cvmfs-cache -c /etc/parrot/ cp -R [DB_DIR]/* . 2> /dev/null \\;  /cvmfs/soft.mugqic/CentOS6/software/blast/ncbi-blast-2.7.1+/bin/blastn [IMPORT_SEARCH_STRATEGY] [EXPORT_SEARCH_STRATEGY] [TASK] [DB] [DBSIZE] [GILIST] [SEQIDLIST] [NEGATIVE_GILIST] [NEGATIVE_SEQIDLIST] [ENTREZ_QUERY] [DB_SOFT_MASK] [DB_HARD_MASK] [SUBJECT] [SUBJECT_LOC] [QUERY] [OUT] [EVALUE] [WORD_SIZE] [GAPOPEN] [GAPEXTEND] [PERC_IDENTITY] [QCOV_HSP_PERC] [MAX_HSPS] [XDROP_UNGAP] [XDROP_GAP] [XDROP_GAP_FINAL] [SEARCHSP] [SUM_STATS] [PENALTY] [REWARD] [fNO_GREEDY] [MIN_RAW_GAPPED_SCORE] [TEMPLATE_TYPE] [TEMPLATE_LENGTH] [DUST] [FILTERING_DB] [WINDOW_MASKER_TAXID] [WINDOW_MASKER_DB] [SOFT_MASKING] [fUNGAPPED] [CULLING_LIMIT] [BEST_HIT_OVERHANG] [BEST_HIT_SCORE_EDGE] [WINDOW_SIZE] [OFF_DIAGONAL_RANGE] [USE_INDEX] [INDEX_NAME] [fLCASE_MASKING] [QUERY_LOC] [STRAND] [fPARSE_DEFLINES] [OUTFMT] [fSHOW_GIS] [NUM_DESCRIPTIONS] [NUM_ALIGNMENTS] [LINE_LENGTH] [fHTML] [MAX_TARGET_SEQS] [NUM_THREADS] [fREMOTE]", "containerimage": {"index": "docker://", "image": "c3genomics/genpipes", "type": "singularity"}, "inputs": [{"command-line-flag": "-db", "description": "BLAST database name", "disables-inputs": ["subject", "subject_loc"], "optional": true, "value-key": "[DB]", "type": "String", "id": "db", "name": "BLAST database name"}, {"description": "directory containing BLAST Archive format in ASN.1 (i.e.: output format 11) and all needed db files", "default-value": ".", "value-key": "[DB_DIR]", "optional": true, "requires-inputs": ["db"], "type": "File", "id": "archive_dir", "name": "Blast Database Directory"}, {"command-line-flag": "-query_loc", "description": "Location on the query sequence in 1-based offsets (Format: start-stop)", "value-key": "[QUERY_LOC]", "optional": true, "type": "String", "id": "query_loc", "name": "query location"}, {"command-line-flag": "-strand", "description": "   Query strand(s) to search against database/subject\n   Default = `both'", "value-key": "[STRAND]", "optional": true, "value-choices": ["both", "minus", "plus"], "type": "String", "id": "strand", "name": "Query Strand to Search"}, {"command-line-flag": "-subject_loc", "description": "Location on the query sequence in 1-based offsets (Format: start-stop)", "disables-inputs": ["db", "gilist", "seqidlist", "negative_gilist", "negative_seqidlist", "db_soft_mask", "db_hard_mask"], "optional": true, "value-key": "[SUBJECT_LOC]", "type": "String", "id": "subject_loc", "name": "Subject Sequence Location"}, {"command-line-flag": "-task", "description": "Task to execute", "value-key": "[TASK]", "optional": true, "value-choices": ["blastn", "blastn-short", "dc-megablast", "megablast", "rmblastn"], "type": "String", "id": "task", "name": "Task Name"}, {"command-line-flag": "-dust", "description": "Filter query sequence with DUST\n  (Format: 'yes', 'level window linker', or   'no' to disable)\n   Default = '20 64 1')", "value-key": "[DUST]", "optional": true, "type": "String", "id": "dust", "name": "DUST Options"}, {"command-line-flag": "-gilist", "description": "Restrict search of database to list of GI's", "disables-inputs": ["negative_gilist", "seqidlist", "negative_seqidlist", "remote", "subject", "subject_loc"], "optional": true, "value-key": "[GILIST]", "type": "String", "id": "gilist", "name": "Restrictive GI List"}, {"command-line-flag": "-seqidlist", "description": "Restrict search of database to list of SeqId's", "disables-inputs": ["gilist", "negative_gilist", "negative_seqidlist", "remote", "subject", "subject_loc"], "optional": true, "value-key": "[SEQIDLIST]", "type": "String", "id": "seqidlist", "name": "Restrictive Sequence Id List"}, {"command-line-flag": "-negative_gilist", "description": "Restrict search of database to everything except the listed GIs", "disables-inputs": ["gilist", "seqidlist", "remote", "subject", "subject_loc"], "optional": true, "value-key": "[NEGATIVE_GILIST]", "type": "String", "id": "negative_gilist", "name": "Exclusive GI List"}, {"command-line-flag": "-negative_seqidlist", "description": "Restrict search of database to everything except the listed SeqIDs", "disables-inputs": ["gilist", "seqidlist", "remote", "subject", "subject_loc"], "optional": true, "value-key": "[NEGATIVE_SEQIDLIST]", "type": "String", "id": "negative_seqidlist", "name": "Exclusive Sequence Id List"}, {"command-line-flag": "-entrez_query", "description": "Restrict search with the given Entrez query", "value-key": "[ENTREZ_QUERY]", "optional": true, "requires-inputs": ["remote"], "type": "String", "id": "entrez_query", "name": "Exclusive Sequence Id List"}, {"command-line-flag": "-db_soft_mask", "description": "Filtering algorithm ID to apply to the BLAST database as soft masking", "disables-inputs": ["db_hard_mask", "subject", "subject_loc"], "optional": true, "value-key": "[DB_SOFT_MASK]", "type": "String", "id": "db_soft_mask", "name": "Soft Mask ID"}, {"command-line-flag": "-db_hard_mask", "description": "Filtering algorithm ID to apply to the BLAST database as hard masking", "disables-inputs": ["db_soft_mask", "subject", "subject_loc"], "optional": true, "value-key": "[DB_HARD_MASK]", "type": "String", "id": "db_hard_mask", "name": "Hard Mask ID"}, {"command-line-flag": "-index_name", "description": "MegaBLAST database index name (deprecated; use only for old style indices)", "value-key": "[INDEX_NAME]", "optional": true, "type": "String", "id": "index_name", "name": "MegaBLAST database index name"}, {"command-line-flag": "-filtering_db", "description": "BLAST database containing filtering elements (i.e.: repeats)", "value-key": "[FILTERING_DB]", "optional": true, "type": "String", "id": "filtering_db", "name": "BLAST filtering database"}, {"command-line-flag": "-window_masker_db", "description": "Enable WindowMasker filtering using this repeats database.", "value-key": "[WINDOW_MASKER_DB]", "optional": true, "type": "String", "id": "window_masker_db", "name": "Window Masker DB"}, {"command-line-flag": "-template_type", "description": "Discontiguous MegaBLAST template type", "value-key": "[TEMPLATE_TYPE]", "optional": true, "requires-inputs": ["template_length"], "value-choices": ["coding", "coding_and_optimal", "optimal"], "type": "String", "id": "template_type", "name": "Discontiguous MegaBLAST template type"}, {"command-line-flag": "-lcase_masking", "description": "Use lower case filtering in query and subject sequence(s)?", "value-key": "[fLCASE_MASKING]", "optional": true, "type": "Flag", "id": "lcase_masking", "name": "Lowercase Filtering"}, {"command-line-flag": "-ungapped", "description": "Perform ungapped alignment only?", "value-key": "[fUNGAPPED]", "optional": true, "type": "Flag", "id": "ungapped", "name": "Ungapped Alignment"}, {"command-line-flag": "-parse_deflines", "description": "Should the query and subject defline(s) be parsed?", "value-key": "[fPARSE_DEFLINES]", "optional": true, "type": "Flag", "id": "parse_deflines", "name": "Parse Deflines"}, {"command-line-flag": "-remote", "description": "Execute search remotely?", "disables-inputs": ["gilist", "seqidlist", "negative_gilist", "negative_seqidlist", "subject_loc", "num_threads"], "optional": true, "value-key": "[fREMOTE]", "type": "Flag", "id": "remote", "name": "Remote Search"}, {"command-line-flag": "-no_greedy", "description": "Use non-greedy dynamic programming extension", "value-key": "[fNO_GREEDY]", "optional": true, "type": "Flag", "id": "no_greedy", "name": "Non-Greedy Dynamic Programming Extension"}, {"command-line-flag": "-use_index", "description": "Use MegaBLAST database index\n  Default 'false'", "value-key": "[USE_INDEX]", "optional": true, "value-choices": ["true", "false"], "type": "String", "id": "use_index", "name": "MegaBLAST Database Index Usage"}, {"command-line-flag": "-soft_masking", "description": "Apply filtering locations as soft masks\n  Default 'true'", "value-key": "[SOFT_MASKING]", "optional": true, "value-choices": ["true", "false"], "type": "String", "id": "soft_masking", "name": "Filtering Locations As Soft Masks"}, {"command-line-flag": "-sum_stats", "description": "Use sum statistics", "value-key": "[SUM_STATS]", "optional": true, "value-choices": ["true", "false"], "type": "String", "id": "sum_stats", "name": "Sum Statistics"}, {"command-line-flag": "-word_size", "description": "Word size for wordfinder algorithm (length of best perfect match)", "value-key": "[WORD_SIZE]", "optional": true, "minimum": 4, "integer": true, "type": "Number", "id": "word_size", "name": "Word Size"}, {"command-line-flag": "-gapopen", "description": "Cost to open a gap", "value-key": "[GAPOPEN]", "optional": true, "integer": true, "type": "Number", "id": "gapopen", "name": "Gap Open Penalty"}, {"command-line-flag": "-gapextend", "description": "Cost to extend a gap", "value-key": "[GAPEXTEND]", "optional": true, "integer": true, "type": "Number", "id": "gapextend", "name": "Gap Extend Penalty"}, {"command-line-flag": "-max_hsps", "description": "Set maximum number of HSPs per subject sequence to save for each query", "value-key": "[MAX_HSPS]", "optional": true, "minimum": 1, "integer": true, "type": "Number", "id": "max_hsps", "name": "Max HSPs Per Subject"}, {"command-line-flag": "-culling_limit", "description": "   If the query range of a hit is enveloped by that of at least this many\n   higher-scoring hits, delete the hit", "value-key": "[CULLING_LIMIT]", "optional": true, "disables-inputs": ["best_hit_overhang", "best_hit_score_edge"], "minimum": 0, "integer": true, "type": "Number", "id": "culling_limit", "name": "Higher Scoring Hit Culling Limit"}, {"command-line-flag": "-max_target_seqs", "description": "   Maximum number of aligned sequences to keep\n   Not applicable for outfmt <= 4\n   Default = `500'", "value-key": "[MAX_TARGET_SEQS]", "optional": true, "disables-inputs": ["num_descriptions", "num_alignments"], "minimum": 1, "integer": true, "type": "Number", "id": "max_target_seqs", "name": "Maximum Target Sequence"}, {"command-line-flag": "-dbsize", "description": "Effective length of the database", "value-key": "[DBSIZE]", "optional": true, "maximum": 255, "integer": true, "type": "Number", "id": "dbsize", "name": "Database Size"}, {"command-line-flag": "-searchsp", "description": "Effective length of the search space", "value-key": "[SEARCHSP]", "optional": true, "maximum": 255, "minimum": 0, "integer": true, "type": "Number", "id": "searchsp", "name": "Search Space Length"}, {"command-line-flag": "-window_size", "description": "Multiple hits window size, use 0 to specify 1-hit algorithm", "value-key": "[WINDOW_SIZE]", "optional": true, "minimum": 0, "integer": true, "type": "Number", "id": "window_size", "name": "Multiple Hits Window Size"}, {"command-line-flag": "-num_threads", "description": "   Number of threads (CPUs) to use in the BLAST search\n   Default = `1'", "value-key": "[NUM_THREADS]", "optional": true, "maximum": 12, "disables-inputs": ["remote"], "minimum": 1, "integer": true, "type": "Number", "id": "num_threads", "name": "Maximum Target Sequence"}, {"command-line-flag": "-penalty", "description": "Penalty for a nucleotide mismatch", "value-key": "[PENALTY]", "optional": true, "maximum": 0, "integer": true, "type": "Number", "id": "penalty", "name": "Nucleotide Mismatch Penalty"}, {"command-line-flag": "-reward", "description": "Reward for a nucleotide match", "value-key": "[REWARD]", "optional": true, "minimum": 0, "integer": true, "type": "Number", "id": "reward", "name": "Nucleotide Match Reward"}, {"command-line-flag": "-window_masker_taxid", "description": "Enable WindowMasker filtering using a Taxonomic ID", "value-key": "[WINDOW_MASKER_TAXID]", "optional": true, "integer": true, "type": "Number", "id": "window_masker_taxid", "name": "Taxonomic ID for WindowMasker Filtering"}, {"command-line-flag": "-template_length", "description": "Discontiguous MegaBLAST template length", "value-key": "[TEMPLATE_LENGTH]", "optional": true, "requires-inputs": ["template_type"], "value-choices": [16, 18, 21], "integer": true, "type": "Number", "id": "template_length", "name": "Discontiguous MegaBLAST Template Length"}, {"command-line-flag": "-min_raw_gapped_score", "description": "Minimum raw gapped score to keep an alignment in the preliminary gapped and traceback stages", "value-key": "[MIN_RAW_GAPPED_SCORE]", "optional": true, "integer": true, "type": "Number", "id": "min_raw_gapped_score", "name": "Minumum Raw Gapped Score"}, {"command-line-flag": "-off_diagonal_range", "description": "   Number of off-diagonals to search for the 2nd hit, use 0 to turn off\n   Default = `0'", "value-key": "[OFF_DIAGONAL_RANGE]", "optional": true, "minimum": 0, "integer": true, "type": "Number", "id": "off_diagonal_range", "name": "Off-Diagonal Range"}, {"command-line-flag": "-evalue", "description": "  Expectation value (E) threshold for saving hits\n  Default = `10'", "value-key": "[EVALUE]", "optional": true, "type": "Number", "id": "evalue", "name": "Expectation Value"}, {"command-line-flag": "-perc_identity", "description": "Percent identity", "value-key": "[PERC_IDENTITY]", "optional": true, "maximum": 100, "minimum": 0, "type": "Number", "id": "perc_identity", "name": "Percent identity"}, {"command-line-flag": "-qcov_hsp_perc", "description": "Percent query coverage per hsp", "value-key": "[QCOV_HSP_PERC]", "optional": true, "maximum": 100, "minimum": 0, "type": "Number", "id": "qcov_hsp_perc", "name": "Percentage Query Coverage"}, {"command-line-flag": "-best_hit_overhang", "description": "Best Hit algorithm overhang value (recommended value: 0.1)", "value-key": "[BEST_HIT_OVERHANG]", "optional": true, "exclusive-maximum": true, "maximum": 0.5, "disables-inputs": ["culling_limit"], "minimum": 0, "exclusive-minimum": true, "type": "Number", "id": "best_hit_overhang", "name": "Best Hit Algorithm Overhang"}, {"command-line-flag": "-best_hit_score_edge", "description": "Best Hit algorithm score edge value (recommended value: 0.1)", "value-key": "[BEST_HIT_SCORE_EDGE]", "optional": true, "exclusive-maximum": true, "maximum": 0.5, "disables-inputs": ["culling_limit"], "minimum": 0, "exclusive-minimum": true, "type": "Number", "id": "best_hit_score_edge", "name": "Best Hit Algorithm Score Edge Value"}, {"command-line-flag": "-xdrop_ungap", "description": "X-dropoff value (in bits) for ungapped extensions", "value-key": "[XDROP_UNGAP]", "optional": true, "type": "Number", "id": "xdrop_ungap", "name": "Ungapped Extensions X-dropoff Value"}, {"command-line-flag": "-xdrop_gap", "description": "X-dropoff value (in bits) for preliminary gapped extensions", "value-key": "[XDROP_GAP]", "optional": true, "type": "Number", "id": "xdrop_gap", "name": "Preiliminary Gapped Extensions X-dropoff Value"}, {"command-line-flag": "-xdrop_gap_final", "description": "X-dropoff value (in bits) for final gapped alignment", "value-key": "[XDROP_GAP_FINAL]", "optional": true, "type": "Number", "id": "xdrop_gap_final", "name": "Final Gapped Extensions X-dropoff Value"}, {"command-line-flag": "-query", "description": "Input file name", "value-key": "[QUERY]", "optional": false, "type": "File", "id": "query", "name": "Query"}, {"command-line-flag": "-subject", "description": "Subject sequence(s) to search", "value-key": "[SUBJECT]", "optional": true, "disables-inputs": ["db", "gilist", "seqidlist", "negative_gilist", "negative_seqidlist", "db_soft_mask", "db_hard_mask"], "type": "File", "id": "subject", "name": "Subject"}, {"command-line-flag": "-import_search_strategy", "description": "Search strategy to use", "value-key": "[IMPORT_SEARCH_STRATEGY]", "optional": true, "disables-inputs": ["export_search_strategy"], "type": "File", "id": "import_search_strategy", "name": "Search Strategy File"}, {"command-line-flag": "-export_search_strategy", "description": "File name to record the search strategy used", "value-key": "[EXPORT_SEARCH_STRATEGY]", "optional": true, "disables-inputs": ["import_search_strategy"], "type": "File", "id": "export_search_strategy", "name": "Search Strategy Record Filename"}, {"command-line-flag": "-show_gis", "description": "Show NCBI GIs in deflines?", "value-key": "[fSHOW_GIS]", "optional": true, "type": "Flag", "id": "show_gis", "name": "Show NCBI GIs"}, {"command-line-flag": "-html", "description": "Produce HTML Output", "value-key": "[fHTML]", "optional": true, "type": "Flag", "id": "html", "name": "Show HTML"}, {"command-line-flag": "-outfmt", "description": "   alignment view options:\n     0 = Pairwise,\n     1 = Query-anchored showing identities,\n     2 = Query-anchored no identities,\n     3 = Flat query-anchored showing identities,\n     4 = Flat query-anchored no identities,\n     5 = BLAST XML,\n     6 = Tabular,\n     7 = Tabular with comment lines,\n     8 = Seqalign (Text ASN.1),\n     9 = Seqalign (Binary ASN.1),\n    10 = Comma-separated values,\n    11 = BLAST archive (ASN.1),\n    12 = Seqalign (JSON),\n    13 = Multiple-file BLAST JSON,\n    14 = Multiple-file BLAST XML2,\n    15 = Single-file BLAST JSON,\n    16 = Single-file BLAST XML2,\n    17 = Sequence Alignment/Map (SAM),\n    18 = Organism Report\n\n   Options 6, 7, 10 and 17 can be additionally configured to produce\n   a custom format specified by space delimited format specifiers.\n   The supported format specifiers for options 6, 7 and 10 are:\n            qseqid means Query Seq-id\n               qgi means Query GI\n              qacc means Query accesion\n           qaccver means Query accesion.version\n              qlen means Query sequence length\n            sseqid means Subject Seq-id\n         sallseqid means All subject Seq-id(s), separated by a ';'\n               sgi means Subject GI\n            sallgi means All subject GIs\n              sacc means Subject accession\n           saccver means Subject accession.version\n           sallacc means All subject accessions\n              slen means Subject sequence length\n            qstart means Start of alignment in query\n              qend means End of alignment in query\n            sstart means Start of alignment in subject\n              send means End of alignment in subject\n              qseq means Aligned part of query sequence\n              sseq means Aligned part of subject sequence\n            evalue means Expect value\n          bitscore means Bit score\n             score means Raw score\n            length means Alignment length\n            pident means Percentage of identical matches\n            nident means Number of identical matches\n          mismatch means Number of mismatches\n          positive means Number of positive-scoring matches\n           gapopen means Number of gap openings\n              gaps means Total number of gaps\n              ppos means Percentage of positive-scoring matches\n            frames means Query and subject frames separated by a '/'\n            qframe means Query frame\n            sframe means Subject frame\n              btop means Blast traceback operations (BTOP)\n            staxid means Subject Taxonomy ID\n          ssciname means Subject Scientific Name\n          scomname means Subject Common Name\n        sblastname means Subject Blast Name\n         sskingdom means Subject Super Kingdom\n           staxids means unique Subject Taxonomy ID(s), separated by a ';'\n                         (in numerical order)\n         sscinames means unique Subject Scientific Name(s), separated by a ';'\n         scomnames means unique Subject Common Name(s), separated by a ';'\n        sblastnames means unique Subject Blast Name(s), separated by a ';'\n                         (in alphabetical order)\n        sskingdoms means unique Subject Super Kingdom(s), separated by a ';'\n                         (in alphabetical order)\n            stitle means Subject Title\n        salltitles means All Subject Title(s), separated by a '<>'\n           sstrand means Subject Strand\n             qcovs means Query Coverage Per Subject\n           qcovhsp means Query Coverage Per HSP\n            qcovus means Query Coverage Per Unique Subject (blastn only)\n   When not provided, the default value is:\n   'qaccver saccver pident length mismatch gapopen qstart qend sstart send\n   evalue bitscore', which is equivalent to the keyword 'std'\n   The supported format specifier for option 17 is:\n                SQ means Include Sequence Data\n                SR means Subject as Reference Seq\n  Default = `0'", "value-key": "[OUTFMT]", "optional": true, "type": "String", "id": "outfmt", "name": "Alignment View Options"}, {"command-line-flag": "-num_descriptions", "description": "   Number of database sequences to show one-line descriptions for\n   Not applicable for outfmt > 4\n   Default = `500'", "value-key": "[NUM_DESCRIPTIONS]", "optional": true, "disables-inputs": ["max_target_seqs"], "minimum": 0, "type": "Number", "id": "num_descriptions", "name": "Number of Sequence Descriptions to Show"}, {"command-line-flag": "-num_alignments", "description": "   Number of database sequences to show alignments for\n   Default = `250'", "value-key": "[NUM_ALIGNMENTS]", "optional": true, "disables-inputs": ["max_target_seqs"], "minimum": 0, "type": "Number", "id": "num_alignments", "name": "Number of Sequence Alignments to Show"}, {"command-line-flag": "-line_length", "description": "   Line length for formatting alignments\n   Not applicable for outfmt > 4\n   Default = `60'", "value-key": "[LINE_LENGTH]", "optional": true, "minimum": 1, "type": "Number", "id": "line_length", "name": "Line Length"}, {"command-line-flag": "-out", "description": "   Output file name", "value-key": "[OUT]", "optional": true, "type": "String", "id": "out", "name": "Output file name"}], "outputfiles": [{"path-template": "[OUT]", "optional": false, "id": "output", "name": "Output File"}], "suggestedresources": {"walltime-estimate": 60, "ram": 1, "cpu-cores": 1}, "name": "blastn", "ark_id": "https://n2t.net/ark:/70798/p72zjj6hg52sw7knzg", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3268715", "title": "CreaPhase1D", "description": "x-ray phase-contrast simulator", "publicationdate": "2019-07-04", "deprecated": false, "downloads": 2980, "author": "Loriane Weber, Simon Rit, Jean Michel L\u00e9tang, Fran\u00e7oise Peyrin, Max Langer", "version": "v0.3", "doi": "10.5281/zenodo.3268715", "schemaversion": "0.5", "container": "docker", "tags": "Boutiques", "errorcodes": [{"code": 1, "description": "Crashed"}], "toolversion": "v0.3", "name": "CreaPhase1D", "commandline": "MYDIR=$PWD; cd /CreaPhase; mkdir [DIROUT]; octave --silent --eval \"SimuPBI_unknown_1D_func('[BASENAME]', [OVERSAMP],  [[DIST]], [ENERGY], [PIXELSIZE], [NBPROJ], [RANGEANGLE], [MODELCTF], [MODELFRESNEL], [ATTFILE], [PHFILE], '[DIROUT]', '[NOISETYPE]', [NOISEAMOUNT])\";  tar czf $MYDIR/[RESULTS] [DIROUT]", "containerimage": {"image": "camarasu/creaphase:0.3", "type": "docker"}, "inputs": [{"command-line-flag": "", "name": "Oversampling of the projections : use 2 or 4", "value-key": "[OVERSAMP]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "oversamp"}, {"command-line-flag": "", "name": "Basename of the result files", "value-key": "[BASENAME]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "basename"}, {"command-line-flag": "", "name": "Distances of propagation (in m), e.g. 0 0.01 0.1 0.20 0.50", "value-key": "[DIST]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "dist"}, {"command-line-flag": "", "name": "Energy of the incoming X-ray beam (in keV)", "value-key": "[ENERGY]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "energy"}, {"command-line-flag": "", "name": "Pixel size of the detector (in um)", "value-key": "[PIXELSIZE]", "optional": false, "type": "String", "id": "pixelSize"}, {"command-line-flag": "", "name": "Number of projections (e.g., 360)", "value-key": "[NBPROJ]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "nbProj"}, {"command-line-flag": "", "name": "Range of the tomography : 180 or 360 degrees", "value-key": "[RANGEANGLE]", "optional": false, "type": "String", "id": "rangeAngle"}, {"command-line-flag": "", "name": "Use 1 if you want to use the CTF model, 0 otherwise", "value-key": "[MODELCTF]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "modelCtf"}, {"command-line-flag": "", "name": "Use 1 if you want to use the Fresnel model, 0 otherwise", "value-key": "[MODELFRESNEL]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "modelFresnel"}, {"command-line-flag": "", "name": "Attenuation map file (in cm^-1)", "value-key": "[ATTFILE]", "optional": false, "command-line-flag-separator": "", "type": "File", "id": "attfile"}, {"command-line-flag": "", "name": "Refrcative index decrement map (delta)", "value-key": "[PHFILE]", "optional": false, "command-line-flag-separator": "", "type": "File", "id": "PHFILE"}, {"command-line-flag": "", "name": "Output directory name", "value-key": "[DIROUT]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "dirOut"}, {"command-line-flag": "", "name": "Use noise='gaussian' (addition of gaussian noise) or noise='poisson' (generation of Poisson noise).", "value-key": "[NOISETYPE]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "noiseType"}, {"command-line-flag": "", "name": "If 'gaussian' (additive noise), please specify the Peak-to-peak Signe-to-noise ratio (PPSNR, in dB). If 'poisson', please specify a scaling factor ranging in [0:1].", "value-key": "[NOISEAMOUNT]", "optional": false, "type": "String", "id": "noiseAmount"}], "outputfiles": [{"description": "archive of the output folder containing execution results, and the output of the command", "value-key": "[RESULTS]", "id": "resultTarball", "optional": false, "path-template": "results.tar.gz", "name": "resultTarball"}], "ark_id": "https://n2t.net/ark:/70798/p7kfm8rbr24mw0s3f6", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3257614", "title": "spark", "description": "SParsity-based Analysis of Reliable K-hubness (SPARK) for brain fMRI functional connectivity", "publicationdate": "2019-06-26", "deprecated": false, "downloads": 2979, "author": "Kangjoo Lee, Jean-Marc Lina, Jean Gotman, Christophe Grova", "version": "v1.2.1", "doi": "10.5281/zenodo.3257614", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": "neuroinformatics"}, "name": "spark", "toolversion": "v1.2.1", "containerimage": {"type": "singularity", "image": "multifunkimlab/spark:1.2.1"}, "commandline": "octave --no-gui --no-init-file -q $SPARK_ROOT/SPARK.m [FMRI_DATA] [MASK] [OUT_DIR] [NB_RESAMPLING] [NETWORK_SCALES] [NB_ITERATIONS] [P_VALUE] [RESAMPLING_METHOD] [BLOCK_WINDOW_LENGTH] [DICT_INIT_METHOD] [SPARSE_CODING_METHOD] [PRESERVE_DC_ATOM] [MAX_PARALLEL_JOBS]", "groups": [{"id": "bootstrap_resampling", "name": "Bootstrap resampling", "members": ["nb_resampling", "resampling_method", "block_window_length"]}, {"id": "sparse_dict_learning", "name": "Sparse dictionary learning", "members": ["network_scales", "nb_iterations", "dict_init_method", "sparse_coding_method", "preserve_dc_atom"]}, {"id": "k_hubness_map_generation", "name": "k-hubness map generation", "members": ["p_value"]}], "outputfiles": [{"id": "result", "name": "Results directory", "description": "Results directory containing:  k-hubness maps, atom maps and intermediate files. (file formats: MINC, NIfTI)", "path-template": "[OUT_DIR]", "optional": false}], "inputs": [{"id": "fmri_data", "name": "fMRI data", "description": "The fMRI data to analyze. (file formats: MINC, NIfTI)", "type": "File", "optional": false, "command-line-flag": "--fmri-data", "value-key": "[FMRI_DATA]"}, {"id": "mask", "name": "Grey-matter mask", "description": "Path to the grey-matter mask. (file formats: MINC, NIfTI)", "type": "File", "optional": false, "command-line-flag": "--mask", "value-key": "[MASK]"}, {"id": "out_dir", "name": "Output name", "description": "The name of the output directory.", "type": "String", "optional": false, "command-line-flag": "--out-dir", "value-key": "[OUT_DIR]"}, {"id": "nb_resampling", "name": "Number of resampling", "description": "Number of bootstrap resampling at the individual level. (recommended: 100)", "type": "Number", "optional": false, "integer": true, "minimum": 2, "command-line-flag": "--nb-resampling", "value-key": "[NB_RESAMPLING]"}, {"id": "network_scales", "name": "Network scales", "description": "Three numbers, respectively: [begin] [step] [end], used to create a regularly-spaced vector. In order to specify a single number, for instance '15', enter the same number for [begin] and [end], as: 15 1 15. This vector of numbers corresponds to the range of network scales to be tested. An optimal network scale is estimated from the specified set of numbers. (recommended: 10 2 30)", "type": "Number", "optional": false, "list": true, "integer": true, "min-list-entries": 3, "max-list-entries": 3, "minimum": 1, "command-line-flag": "--network-scales", "value-key": "[NETWORK_SCALES]"}, {"id": "nb_iterations", "name": "Number of iterations", "description": "Number of iterations for the sparse dictionary learning.  (recommended: 20)", "type": "Number", "optional": false, "integer": true, "minimum": 2, "command-line-flag": "--nb-iterations", "value-key": "[NB_ITERATIONS]"}, {"id": "p_value", "name": "P-Value", "description": "Significance level, using a Z-test, for removing inconsistent elements in the average sparse coefficients (considered as the Gaussian noise) after spatial clustering (using a threshold).", "type": "Number", "optional": false, "minimum": 0, "maximum": 1, "command-line-flag": "--p-value", "value-key": "[P_VALUE]"}, {"id": "resampling_method", "name": "Resampling method", "description": "Method (from NIAK) used to resample the data under the null hypothesis. Note: If 'CBB' is selected, the option --block-window-length is used. [CBB]: Circular-block-bootstrap sample of multiple time series. [AR1B]: Bootstrap sample of multiple time series based on a semiparametric scheme mixing an auto-regressive temporal model and i.i.d. bootstrap of the 'innovations'. [AR1G]: (Bootstrap sample of multiple time series based on a parametric model of Gaussian data with arbitrary spatial correlations and first-order auto-regressive temporal correlations.", "type": "String", "optional": true, "value-choices": ["CBB", "AR1B", "AR1G"], "value-disables": {"CBB": [], "AR1B": ["block_window_length"], "AR1G": ["block_window_length"]}, "value-requires": {"CBB": ["block_window_length"], "AR1B": [], "AR1G": []}, "default-value": "CBB", "command-line-flag": "--resampling-method", "value-key": "[RESAMPLING_METHOD]"}, {"id": "block_window_length", "name": "Block window length", "description": "Three numbers, respectively: [begin] [step] [end], used to create a regularly-spaced vector. In order to specify a single number, for instance '15', enter the same number for [begin] and [end], as: 15 1 15. A number in this vector corresponds to a window length used in the circular block bootstrap. The unit of the window length is \u2018time-point\u2019 with each time-point indicating a 3D scan at each TR. If multiple numbers are specified, then a number is randomly selected from the list at each resampling. It is recommended to use a minimum of sqrt(T), where T is the total number of time points in the fMRI time-course. It is also recommended to randomize the window length to reduce a bias by window size.", "type": "Number", "optional": true, "list": true, "integer": true, "min-list-entries": 3, "max-list-entries": 3, "minimum": 1, "default-value": [10, 1, 30], "command-line-flag": "--block-window-length", "value-key": "[BLOCK_WINDOW_LENGTH]"}, {"id": "dict_init_method", "name": "Dictionary initialization method", "description": "If 'GivenMatrix' is selected, then the dictionary will be initialized by a random permutation of the raw data obtained in step 1. If 'DataElements' is selected, then the dictionary will be initialized by the first N (number of atoms) columns in the raw data obtained in step 1.", "type": "String", "optional": true, "value-choices": ["GivenMatrix", "DataElements"], "default-value": "GivenMatrix", "command-line-flag": "--dict-init-method", "value-key": "[DICT_INIT_METHOD]"}, {"id": "sparse_coding_method", "name": "Sparse coding method", "description": "Sparse coding method for the sparse dictionary learning.", "type": "String", "optional": true, "value-choices": ["OMP", "Thresholding"], "default-value": "Thresholding", "command-line-flag": "--sparse-coding-method", "value-key": "[SPARSE_CODING_METHOD]"}, {"id": "preserve_dc_atom", "name": "Perserve first atom", "description": "If set, then the first atom will be set to a constant and will never change, while all the other atoms will be trained and updated.", "type": "Flag", "optional": true, "command-line-flag": "--preserve-dc-atom", "value-key": "[PRESERVE_DC_ATOM]"}, {"id": "max_parallel_jobs", "name": "Number of parallel jobs", "description": "Maximum number of jobs to run in parallel.", "type": "Number", "optional": true, "default-value": 12, "command-line-flag": "--max-parallel-jobs", "value-key": "[MAX_PARALLEL_JOBS]"}], "suggestedresources": {"cpu-cores": 2, "ram": 12, "walltime-estimate": 100000}, "ark_id": "https://n2t.net/ark:/70798/p7t4hp2ms3f9r2wtgd", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3239451", "title": "blastp", "description": "Protein-Protein BLAST 2.7.1+", "publicationdate": "2019-06-05", "deprecated": false, "downloads": 2977, "author": "Altschul et al.", "version": "v2.7.1", "doi": "10.5281/zenodo.3239451", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["bioinformatics", "blast"]}, "toolversion": "v2.7.1", "tests": [{"invocation": {"outfmt": "5", "evalue": 0.001, "db": "uniprotmini.fasta", "query": "test1_query.fasta", "max_target_seqs": 10, "out": "blastp.out"}, "name": "test1", "assertions": {"output-files": [{"id": "output", "md5-reference": "049ea2f2b7e3fbe9a0c7d36a8e1c749c"}], "exit-code": 0}}], "commandline": "init_genpipes -a /tmp/$USER/cvmfs-cache -c /etc/parrot/ cp -R [DB_DIR]/* . 2> /dev/null \\; /cvmfs/soft.mugqic/CentOS6/software/blast/ncbi-blast-2.7.1+/bin/blastp [IMPORT_SEARCH_STRATEGY] [EXPORT_SEARCH_STRATEGY] [TASK] [DB] [DBSIZE] [GILIST] [SEQIDLIST] [NEGATIVE_GILIST] [NEGATIVE_SEQIDLIST] [ENTREZ_QUERY] [DB_SOFT_MASK] [DB_HARD_MASK] [SUBJECT] [SUBJECT_LOC] [QUERY] [OUT] [EVALUE] [WORD_SIZE] [GAPOPEN] [GAPEXTEND] [QCOV_HSP_PERC] [MAX_HSPS] [XDROP_UNGAP] [XDROP_GAP] [XDROP_GAP_FINAL] [SEARCHSP] [SUM_STATS] [SEG] [SOFT_MASKING] [MATRIX] [THRESHOLD] [CULLING_LIMIT] [BEST_HIT_OVERHANG] [BEST_HIT_SCORE_EDGE] [WINDOW_SIZE] [fLCASE_MASKING] [QUERY_LOC] [fPARSE_DEFLINES] [OUTFMT] [fSHOW_GIS] [NUM_DESCRIPTIONS] [NUM_ALIGNMENTS] [LINE_LENGTH] [fHTML] [MAX_TARGET_SEQS] [NUM_THREADS] [fUNGAPPED] [fREMOTE] [COMP_BASED_STATS] [fUSE_SW_TBACK]", "containerimage": {"index": "docker://", "image": "c3genomics/genpipes", "type": "singularity"}, "inputs": [{"command-line-flag": "-db", "description": "BLAST database name", "disables-inputs": ["subject", "subject_loc"], "optional": true, "value-key": "[DB]", "type": "String", "id": "db", "name": "BLAST database name"}, {"description": "directory containing BLAST Archive format in ASN.1 (i.e.: output format 11) and all needed db files", "default-value": ".", "value-key": "[DB_DIR]", "optional": true, "requires-inputs": ["db"], "type": "File", "id": "archive_dir", "name": "Blast Database Directory"}, {"command-line-flag": "-query_loc", "description": "Location on the query sequence in 1-based offsets (Format: start-stop)", "value-key": "[QUERY_LOC]", "optional": true, "type": "String", "id": "query_loc", "name": "query location"}, {"command-line-flag": "-subject_loc", "description": "Location on the query sequence in 1-based offsets (Format: start-stop)", "disables-inputs": ["db", "gilist", "seqidlist", "negative_gilist", "negative_seqidlist", "db_soft_mask", "db_hard_mask"], "optional": true, "value-key": "[SUBJECT_LOC]", "type": "String", "id": "subject_loc", "name": "Subject Sequence Location"}, {"command-line-flag": "-task", "description": "Task to execute", "value-key": "[TASK]", "optional": true, "value-choices": ["blastp", "blastp-fast", "blastp-short"], "type": "String", "id": "task", "name": "Task Name"}, {"command-line-flag": "-matrix", "description": "Scoring matrix name (normally BLOSUM62)", "value-key": "[MATRIX]", "optional": true, "type": "String", "id": "matrix", "name": "Scoring matrix name"}, {"command-line-flag": "-comp_based_stats", "description": "Use composition-based statistics:\n       D or d: default (equivalent to 2 )\n       0 or F or f: No composition-based statistics\n       1: Composition-based statistics as in NAR 29:2994-3005, 2001\n       2 or T or t : Composition-based score adjustment as in Bioinformatics\n   21:902-911, 2005, conditioned on sequence properties\n       3: Composition-based score adjustment as in Bioinformatics 21:902-911,\n 2005, unconditionally\nDefault = `2'", "value-key": "[COMP_BASED_STATS]", "optional": true, "value-choices": ["D", "d", "0", "F", "f", "1", "2", "T", "t", "3"], "type": "String", "id": "comp_based_stats", "name": "Composition-based statistics mode"}, {"command-line-flag": "-seg", "description": "Filter query sequence with SEG", "value-key": "[SEG]", "optional": true, "value-choices": ["yes", "window locut hicut", "no"], "type": "String", "id": "seg", "name": "SEG Options"}, {"command-line-flag": "-gilist", "description": "Restrict search of database to list of GI's", "disables-inputs": ["negative_gilist", "seqidlist", "negative_seqidlist", "remote", "subject", "subject_loc"], "optional": true, "value-key": "[GILIST]", "type": "String", "id": "gilist", "name": "Restrictive GI List"}, {"command-line-flag": "-seqidlist", "description": "Restrict search of database to list of SeqId's", "disables-inputs": ["gilist", "negative_gilist", "negative_seqidlist", "remote", "subject", "subject_loc"], "optional": true, "value-key": "[SEQIDLIST]", "type": "String", "id": "seqidlist", "name": "Restrictive Sequence Id List"}, {"command-line-flag": "-negative_gilist", "description": "Restrict search of database to everything except the listed GIs", "disables-inputs": ["gilist", "seqidlist", "remote", "subject", "subject_loc"], "optional": true, "value-key": "[NEGATIVE_GILIST]", "type": "String", "id": "negative_gilist", "name": "Exclusive GI List"}, {"command-line-flag": "-negative_seqidlist", "description": "Restrict search of database to everything except the listed SeqIDs", "disables-inputs": ["gilist", "seqidlist", "remote", "subject", "subject_loc"], "optional": true, "value-key": "[NEGATIVE_SEQIDLIST]", "type": "String", "id": "negative_seqidlist", "name": "Exclusive Sequence Id List"}, {"command-line-flag": "-entrez_query", "description": "Restrict search with the given Entrez query", "value-key": "[ENTREZ_QUERY]", "optional": true, "requires-inputs": ["remote"], "type": "String", "id": "entrez_query", "name": "Exclusive Sequence Id List"}, {"command-line-flag": "-db_soft_mask", "description": "Filtering algorithm ID to apply to the BLAST database as soft masking", "disables-inputs": ["db_hard_mask", "subject", "subject_loc"], "optional": true, "value-key": "[DB_SOFT_MASK]", "type": "String", "id": "db_soft_mask", "name": "Soft Mask ID"}, {"command-line-flag": "-db_hard_mask", "description": "Filtering algorithm ID to apply to the BLAST database as hard masking", "disables-inputs": ["db_soft_mask", "subject", "subject_loc"], "optional": true, "value-key": "[DB_HARD_MASK]", "type": "String", "id": "db_hard_mask", "name": "Hard Mask ID"}, {"command-line-flag": "-lcase_masking", "description": "Use lower case filtering in query and subject sequence(s)?", "value-key": "[fLCASE_MASKING]", "optional": true, "type": "Flag", "id": "lcase_masking", "name": "Lowercase Filtering"}, {"command-line-flag": "-ungapped", "description": "Perform ungapped alignment only?", "value-key": "[fUNGAPPED]", "optional": true, "type": "Flag", "id": "ungapped", "name": "Ungapped Alignment"}, {"command-line-flag": "-parse_deflines", "description": "Should the query and subject defline(s) be parsed?", "value-key": "[fPARSE_DEFLINES]", "optional": true, "type": "Flag", "id": "parse_deflines", "name": "Parse Deflines"}, {"command-line-flag": "-remote", "description": "Execute search remotely?", "disables-inputs": ["gilist", "seqidlist", "negative_gilist", "negative_seqidlist", "subject_loc", "num_threads"], "optional": true, "value-key": "[fREMOTE]", "type": "Flag", "id": "remote", "name": "Remote Search"}, {"command-line-flag": "-use_sw_tback", "description": "Compute locally optimal Smith-Waterman alignments?", "value-key": "[fUSE_SW_TBACK]", "optional": true, "type": "Flag", "id": "use_sw_tback", "name": "Locally Optimal Smith-Waterman Alignments"}, {"command-line-flag": "-soft_masking", "description": "Apply filtering locations as soft masks", "value-key": "[SOFT_MASKING]", "optional": true, "value-choices": ["true", "false"], "type": "String", "id": "soft_masking", "name": "Filtering Locations As Soft Masks"}, {"command-line-flag": "-sum_stats", "description": "Use sum statistics", "value-key": "[SUM_STATS]", "optional": true, "value-choices": ["true", "false"], "type": "String", "id": "sum_stats", "name": "Sum Statistics"}, {"command-line-flag": "-word_size", "description": "Word size for wordfinder algorithm", "value-key": "[WORD_SIZE]", "optional": true, "minimum": 2, "integer": true, "type": "Number", "id": "word_size", "name": "Word Size"}, {"command-line-flag": "-gapopen", "description": "Cost to open a gap", "value-key": "[GAPOPEN]", "optional": true, "integer": true, "type": "Number", "id": "gapopen", "name": "Gap Open Penalty"}, {"command-line-flag": "-gapextend", "description": "Cost to extend a gap", "value-key": "[GAPEXTEND]", "optional": true, "integer": true, "type": "Number", "id": "gapextend", "name": "Gap Extend Penalty"}, {"command-line-flag": "-max_hsps", "description": "Set maximum number of HSPs per subject sequence to save for each query", "value-key": "[MAX_HSPS]", "optional": true, "minimum": 1, "integer": true, "type": "Number", "id": "max_hsps", "name": "Max HSPs Per Subject"}, {"command-line-flag": "-culling_limit", "description": "   If the query range of a hit is enveloped by that of at least this many\n   higher-scoring hits, delete the hit", "value-key": "[CULLING_LIMIT]", "optional": true, "disables-inputs": ["best_hit_overhang", "best_hit_score_edge"], "minimum": 0, "integer": true, "type": "Number", "id": "culling_limit", "name": "Higher Scoring Hit Culling Limit"}, {"command-line-flag": "-max_target_seqs", "description": "   Maximum number of aligned sequences to keep\n   Not applicable for outfmt <= 4\n   Default = `500'", "value-key": "[MAX_TARGET_SEQS]", "optional": true, "disables-inputs": ["num_descriptions", "num_alignments"], "minimum": 1, "integer": true, "type": "Number", "id": "max_target_seqs", "name": "Maximum Target Sequence"}, {"command-line-flag": "-dbsize", "description": "Effective length of the database", "value-key": "[DBSIZE]", "optional": true, "maximum": 255, "integer": true, "type": "Number", "id": "dbsize", "name": "Database Size"}, {"command-line-flag": "-searchsp", "description": "Effective length of the search space", "value-key": "[SEARCHSP]", "optional": true, "maximum": 255, "minimum": 0, "integer": true, "type": "Number", "id": "searchsp", "name": "Search Space Length"}, {"command-line-flag": "-window_size", "description": "Multiple hits window size, use 0 to specify 1-hit algorithm", "value-key": "[WINDOW_SIZE]", "optional": true, "minimum": 0, "integer": true, "type": "Number", "id": "window_size", "name": "Multiple Hits Window Size"}, {"command-line-flag": "-num_threads", "description": "   Number of threads (CPUs) to use in the BLAST search\n   Default = `1'", "value-key": "[NUM_THREADS]", "optional": true, "maximum": 12, "disables-inputs": ["remote"], "minimum": 1, "integer": true, "type": "Number", "id": "num_threads", "name": "Maximum Target Sequence"}, {"command-line-flag": "-evalue", "description": "  Expectation value (E) threshold for saving hits\n  Default = `10'", "value-key": "[EVALUE]", "optional": true, "type": "Number", "id": "evalue", "name": "Expectation Value"}, {"command-line-flag": "-threshold", "description": "Minimum word score such that the word is added to the BLAST lookup table", "value-key": "[THRESHOLD]", "optional": true, "minimum": 0, "type": "Number", "id": "threshold", "name": "Minimum word score threshold"}, {"command-line-flag": "-qcov_hsp_perc", "description": "Percent query coverage per hsp", "value-key": "[QCOV_HSP_PERC]", "optional": true, "maximum": 100, "minimum": 0, "type": "Number", "id": "qcov_hsp_perc", "name": "Percentage Query Coverage"}, {"command-line-flag": "-best_hit_overhang", "description": "Best Hit algorithm overhang value (recommended value: 0.1)", "value-key": "[BEST_HIT_OVERHANG]", "optional": true, "exclusive-maximum": true, "maximum": 0.5, "disables-inputs": ["culling_limit"], "minimum": 0, "exclusive-minimum": true, "type": "Number", "id": "best_hit_overhang", "name": "Best Hit Algorithm Overhang"}, {"command-line-flag": "-best_hit_score_edge", "description": "Best Hit algorithm score edge value (recommended value: 0.1)", "value-key": "[BEST_HIT_SCORE_EDGE]", "optional": true, "exclusive-maximum": true, "maximum": 0.5, "disables-inputs": ["culling_limit"], "minimum": 0, "exclusive-minimum": true, "type": "Number", "id": "best_hit_score_edge", "name": "Best Hit Algorithm Score Edge Value"}, {"command-line-flag": "-xdrop_ungap", "description": "X-dropoff value (in bits) for ungapped extensions", "value-key": "[XDROP_UNGAP]", "optional": true, "type": "Number", "id": "xdrop_ungap", "name": "Ungapped Extensions X-dropoff Value"}, {"command-line-flag": "-xdrop_gap", "description": "X-dropoff value (in bits) for preliminary gapped extensions", "value-key": "[XDROP_GAP]", "optional": true, "type": "Number", "id": "xdrop_gap", "name": "Preiliminary Gapped Extensions X-dropoff Value"}, {"command-line-flag": "-xdrop_gap_final", "description": "X-dropoff value (in bits) for final gapped alignment", "value-key": "[XDROP_GAP_FINAL]", "optional": true, "type": "Number", "id": "xdrop_gap_final", "name": "Final Gapped Extensions X-dropoff Value"}, {"command-line-flag": "-query", "description": "Input file name", "value-key": "[QUERY]", "optional": false, "type": "File", "id": "query", "name": "Query"}, {"command-line-flag": "-subject", "description": "Subject sequence(s) to search", "value-key": "[SUBJECT]", "optional": true, "disables-inputs": ["db", "gilist", "seqidlist", "negative_gilist", "negative_seqidlist", "db_soft_mask", "db_hard_mask"], "type": "File", "id": "subject", "name": "Subject"}, {"command-line-flag": "-import_search_strategy", "description": "Search strategy to use", "value-key": "[IMPORT_SEARCH_STRATEGY]", "optional": true, "disables-inputs": ["export_search_strategy"], "type": "File", "id": "import_search_strategy", "name": "Search Strategy File"}, {"command-line-flag": "-export_search_strategy", "description": "File name to record the search strategy used", "value-key": "[EXPORT_SEARCH_STRATEGY]", "optional": true, "disables-inputs": ["import_search_strategy"], "type": "File", "id": "export_search_strategy", "name": "Search Strategy Record Filename"}, {"command-line-flag": "-show_gis", "description": "Show NCBI GIs in deflines?", "value-key": "[fSHOW_GIS]", "optional": true, "type": "Flag", "id": "show_gis", "name": "Show NCBI GIs"}, {"command-line-flag": "-html", "description": "Produce HTML Output", "value-key": "[fHTML]", "optional": true, "type": "Flag", "id": "html", "name": "Show HTML"}, {"command-line-flag": "-outfmt", "description": "   alignment view options:\n     0 = Pairwise,\n     1 = Query-anchored showing identities,\n     2 = Query-anchored no identities,\n     3 = Flat query-anchored showing identities,\n     4 = Flat query-anchored no identities,\n     5 = BLAST XML,\n     6 = Tabular,\n     7 = Tabular with comment lines,\n     8 = Seqalign (Text ASN.1),\n     9 = Seqalign (Binary ASN.1),\n    10 = Comma-separated values,\n    11 = BLAST archive (ASN.1),\n    12 = Seqalign (JSON),\n    13 = Multiple-file BLAST JSON,\n    14 = Multiple-file BLAST XML2,\n    15 = Single-file BLAST JSON,\n    16 = Single-file BLAST XML2,\n    17 = Sequence Alignment/Map (SAM),\n    18 = Organism Report\n\n   Options 6, 7, 10 and 17 can be additionally configured to produce\n   a custom format specified by space delimited format specifiers.\n   The supported format specifiers for options 6, 7 and 10 are:\n            qseqid means Query Seq-id\n               qgi means Query GI\n              qacc means Query accesion\n           qaccver means Query accesion.version\n              qlen means Query sequence length\n            sseqid means Subject Seq-id\n         sallseqid means All subject Seq-id(s), separated by a ';'\n               sgi means Subject GI\n            sallgi means All subject GIs\n              sacc means Subject accession\n           saccver means Subject accession.version\n           sallacc means All subject accessions\n              slen means Subject sequence length\n            qstart means Start of alignment in query\n              qend means End of alignment in query\n            sstart means Start of alignment in subject\n              send means End of alignment in subject\n              qseq means Aligned part of query sequence\n              sseq means Aligned part of subject sequence\n            evalue means Expect value\n          bitscore means Bit score\n             score means Raw score\n            length means Alignment length\n            pident means Percentage of identical matches\n            nident means Number of identical matches\n          mismatch means Number of mismatches\n          positive means Number of positive-scoring matches\n           gapopen means Number of gap openings\n              gaps means Total number of gaps\n              ppos means Percentage of positive-scoring matches\n            frames means Query and subject frames separated by a '/'\n            qframe means Query frame\n            sframe means Subject frame\n              btop means Blast traceback operations (BTOP)\n            staxid means Subject Taxonomy ID\n          ssciname means Subject Scientific Name\n          scomname means Subject Common Name\n        sblastname means Subject Blast Name\n         sskingdom means Subject Super Kingdom\n           staxids means unique Subject Taxonomy ID(s), separated by a ';'\n                         (in numerical order)\n         sscinames means unique Subject Scientific Name(s), separated by a ';'\n         scomnames means unique Subject Common Name(s), separated by a ';'\n        sblastnames means unique Subject Blast Name(s), separated by a ';'\n                         (in alphabetical order)\n        sskingdoms means unique Subject Super Kingdom(s), separated by a ';'\n                         (in alphabetical order)\n            stitle means Subject Title\n        salltitles means All Subject Title(s), separated by a '<>'\n           sstrand means Subject Strand\n             qcovs means Query Coverage Per Subject\n           qcovhsp means Query Coverage Per HSP\n            qcovus means Query Coverage Per Unique Subject (blastn only)\n   When not provided, the default value is:\n   'qaccver saccver pident length mismatch gapopen qstart qend sstart send\n   evalue bitscore', which is equivalent to the keyword 'std'\n   The supported format specifier for option 17 is:\n                SQ means Include Sequence Data\n                SR means Subject as Reference Seq\n  Default = `0'", "value-key": "[OUTFMT]", "optional": true, "type": "String", "id": "outfmt", "name": "Alignment View Options"}, {"command-line-flag": "-num_descriptions", "description": "   Number of database sequences to show one-line descriptions for\n   Not applicable for outfmt > 4\n   Default = `500'", "value-key": "[NUM_DESCRIPTIONS]", "optional": true, "disables-inputs": ["max_target_seqs"], "minimum": 0, "type": "Number", "id": "num_descriptions", "name": "Number of Sequence Descriptions to Show"}, {"command-line-flag": "-num_alignments", "description": "   Number of database sequences to show alignments for\n   Default = `250'", "value-key": "[NUM_ALIGNMENTS]", "optional": true, "disables-inputs": ["max_target_seqs"], "minimum": 0, "type": "Number", "id": "num_alignments", "name": "Number of Sequence Alignments to Show"}, {"command-line-flag": "-line_length", "description": "   Line length for formatting alignments\n   Not applicable for outfmt > 4\n   Default = `60'", "value-key": "[LINE_LENGTH]", "optional": true, "minimum": 1, "type": "Number", "id": "line_length", "name": "Line Length"}, {"command-line-flag": "-out", "description": "   Output file name", "value-key": "[OUT]", "optional": true, "type": "String", "id": "out", "name": "Output file name"}], "outputfiles": [{"path-template": "[OUT]", "optional": false, "id": "output", "name": "Output File"}], "suggestedresources": {"walltime-estimate": 60, "ram": 1, "cpu-cores": 1}, "name": "blastp", "ark_id": "https://n2t.net/ark:/70798/p7ph3d21z6p7q0qwqd", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3245387", "title": "AQUA", "description": "automatic quality improvment for multiple sequence alignment.", "publicationdate": "2019-06-13", "deprecated": false, "downloads": 2976, "author": "Muller J, Creevey CJ, Thompson JD, Arendt D, Bork P.", "version": "v1.1", "doi": "10.5281/zenodo.3245387", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["bioinformatics", "AQUA"]}, "toolversion": "v1.1", "tests": [{"invocation": {"input": "uniprotminier.fasta"}, "name": "test1", "assertions": {"output-files": [{"id": "outmafft_rascal", "md5-reference": "4b003bebd3fb9722152f65ab5d17c434"}], "exit-code": 0}}], "commandline": "AQUA.tcl [INPUT] [OUTPUT_DIR]", "containerimage": {"index": "shub://", "image": "bioinformatics-group/aqua-singularity-recipe", "type": "singularity"}, "inputs": [{"description": "A file containing the input sequence in fasta format", "value-key": "[INPUT]", "optional": false, "type": "File", "id": "input", "name": "Input Sequence"}, {"description": "The directory where the results are stored. The default location is the same directory as the input sequence.", "default-value": ".", "value-key": "[OUTPUT_DIR]", "optional": false, "type": "File", "id": "output_dir", "name": "Output Directory"}], "outputfiles": [{"path-template": "[OUTPUT_DIR]/[INPUT].muscle", "optional": false, "id": "outmuscle", "name": "Output of muscle results"}, {"path-template": "[OUTPUT_DIR]/[INPUT].mafft", "optional": false, "id": "outmafft", "name": "Output of mafft results"}, {"path-template": "[OUTPUT_DIR]/[INPUT].muscle.rascal", "optional": false, "id": "outmuscle_rascal", "name": "Output of muscle and rascal results"}, {"path-template": "[OUTPUT_DIR]/[INPUT].mafft.rascal", "optional": false, "id": "outmafft_rascal", "name": "Output of mafft and rascal results"}, {"path-template": "[OUTPUT_DIR]/[INPUT].muscle.normd", "optional": false, "id": "outmuscle_normd", "name": "Output of muscle and normd results"}, {"path-template": "[OUTPUT_DIR]/[INPUT].mafft.normd", "optional": false, "id": "outmafft_normd", "name": "Output of mafft and normd results"}, {"path-template": "[OUTPUT_DIR]/[INPUT].muscle.rascal.normd", "optional": false, "id": "outmuscle_rascal_normd", "name": "Output of muscle, rascal and normd results"}, {"path-template": "[OUTPUT_DIR]/[INPUT].mafft.rascal.normd", "optional": false, "id": "outmafft_rascal_normd", "name": "Output of mafft, rascal and normd results"}, {"path-template": "[OUTPUT_DIR]/[INPUT].best", "optional": false, "id": "outbest", "name": "Output of best results"}], "suggestedresources": {"walltime-estimate": 60, "ram": 1, "cpu-cores": 1}, "name": "AQUA", "ark_id": "https://n2t.net/ark:/70798/p7dzh97dx34n001w08", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3269322", "title": "CreaPhase3Wires", "description": "x-ray phase-contrast simulator", "publicationdate": "2019-07-05", "deprecated": false, "downloads": 2962, "author": "Loriane Weber, Simon Rit, Jean Michel L\u00e9tang, Fran\u00e7oise Peyrin, Max Langer", "version": "v0.3", "doi": "10.5281/zenodo.3269322", "schemaversion": "0.5", "container": "docker", "tags": "Boutiques", "errorcodes": [{"code": 1, "description": "Crashed"}], "toolversion": "v0.3", "name": "CreaPhase3Wires", "commandline": "MYDIR=$PWD; cd /CreaPhase; mkdir [DIROUT]; octave --silent --eval \"SimuPBI_3WiresPhant_func('[VERS]', [OVERSAMP], '[BASENAME]', [[DIST]], [ENERGY], [PIXELSIZE], [NBPROJ], [RANGEANGLE], [MODELCTF], [MODELFRESNEL], [HEIGHT], '[DIROUT]', '[NOISETYPE]', [NOISEAMOUNT])\";  tar czf $MYDIR/[RESULTS] [DIROUT]", "containerimage": {"image": "camarasu/creaphase:0.3", "type": "docker"}, "inputs": [{"command-line-flag": "", "name": "Set it to 'Radon' OR 'Analytical'to calculate projections accordingly", "value-key": "[VERS]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "vers"}, {"command-line-flag": "", "name": "Oversampling of the projections : use 2 or 4", "value-key": "[OVERSAMP]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "oversamp"}, {"command-line-flag": "", "name": "Basename of the result files", "value-key": "[BASENAME]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "basename"}, {"command-line-flag": "", "name": "Distances of propagation (in m), e.g. 0 0.01 0.1 0.20 0.50", "value-key": "[DIST]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "dist"}, {"command-line-flag": "", "name": "Energy of the incoming X-ray beam (in keV)", "value-key": "[ENERGY]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "energy"}, {"command-line-flag": "", "name": "Pixel size of the detector (in um)", "value-key": "[PIXELSIZE]", "optional": false, "type": "String", "id": "pixelSize"}, {"command-line-flag": "", "name": "Number of projections (e.g., 360)", "value-key": "[NBPROJ]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "nbProj"}, {"command-line-flag": "", "name": "Range of the tomography : 180 or 360 degrees", "value-key": "[RANGEANGLE]", "optional": false, "type": "String", "id": "rangeAngle"}, {"command-line-flag": "", "name": "Use 1 if you want to use the CTF model, 0 otherwise", "value-key": "[MODELCTF]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "modelCtf"}, {"command-line-flag": "", "name": "Use 1 if you want to use the Fresnel model, 0 otherwise", "value-key": "[MODELFRESNEL]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "modelFresnel"}, {"command-line-flag": "", "name": "height of the object. If height == 1, the simulation is computed in 1D. If height >=2 , the simulation turns into 2D.", "value-key": "[HEIGHT]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "height"}, {"command-line-flag": "", "name": "Output directory name", "value-key": "[DIROUT]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "dirOut"}, {"command-line-flag": "", "name": "Use noise='gaussian' (addition of gaussian noise) or noise='poisson' (generation of Poisson noise).", "value-key": "[NOISETYPE]", "optional": false, "command-line-flag-separator": "", "type": "String", "id": "noiseType"}, {"command-line-flag": "", "name": "If 'gaussian' (additive noise), please specify the Peak-to-peak Signe-to-noise ratio (PPSNR, in dB). If 'poisson', please specify a scaling factor ranging in [0:1].", "value-key": "[NOISEAMOUNT]", "optional": false, "type": "String", "id": "noiseAmount"}], "outputfiles": [{"description": "archive of the output folder containing execution results, and the output of the command", "value-key": "[RESULTS]", "id": "resultTarball", "optional": false, "path-template": "results.tar.gz", "name": "resultTarball"}], "ark_id": "https://n2t.net/ark:/70798/p7gk1t01w52976xpzz", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3384924", "title": "animaMSExamPreparation", "description": "Registers and pre-processes input images of an MS patient sequence onto a common reference.", "publicationdate": "2019-09-03", "deprecated": false, "downloads": 2878, "author": "Francesca Galassi", "version": "v0.1.2", "doi": "10.5281/zenodo.3384924", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "multiple-sclerosis"]}, "inputs": [{"command-line-flag": "-r", "description": "Path to the MS patient reference image (usually FLAIR at first time point)", "value-key": "[REFERENCE]", "optional": false, "type": "File", "id": "reference", "name": "reference"}, {"command-line-flag": "-f", "description": "Path to the MS patient FLAIR image to register", "value-key": "[FLAIR]", "optional": false, "type": "File", "id": "flair", "name": "flair"}, {"command-line-flag": "-t", "description": "Path to the MS patient T1 image to register", "value-key": "[T1]", "optional": false, "type": "File", "id": "t1", "name": "t1"}, {"command-line-flag": "-g", "description": "Path to the MS patient T1-Gd image to register", "value-key": "[T1_GD]", "optional": true, "type": "File", "id": "t1_gd", "name": "t1_gd"}, {"command-line-flag": "-T", "description": "Path to the MS patient T2 image to register", "value-key": "[T2]", "optional": true, "type": "File", "id": "t2", "name": "t2"}, {"command-line-flag": "-o", "description": "Path to output image", "value-key": "[OUTPUTFOLDER]", "optional": false, "type": "String", "id": "outputFolder", "name": "outputFolder"}], "commandline": "cd /music/music_v3.2/ && python3 /music/music_v3.2/animaMSExamPreparation.py [REFERENCE] [FLAIR] [T1] [T1_GD] [T2] [OUTPUTFOLDER]", "toolversion": "v0.1.2", "containerimage": {"index": "index.docker.io", "image": "arthursw/anima-ms:v1", "type": "docker"}, "outputfiles": [{"description": "Preprocessed flair image file", "id": "preprocessed_flair_image", "optional": false, "path-template": "[FLAIR]_preprocessed.nrrd", "path-template-stripped-extensions": [".nii.gz", ".nii"], "name": "Preprocessed flair image"}, {"description": "Preprocessed T1 image file", "id": "preprocessed_t1_image", "optional": false, "path-template": "[T1]_preprocessed.nrrd", "path-template-stripped-extensions": [".nii.gz", ".nii"], "name": "Preprocessed T1 image"}, {"description": "Preprocessed T1-Gd image file", "id": "preprocessed_t1_gd_image", "optional": true, "path-template": "[T1_GD]_preprocessed.nrrd", "path-template-stripped-extensions": [".nii.gz", ".nii"], "name": "Preprocessed T1-Gd image"}, {"description": "Preprocessed T2 image file", "id": "preprocessed_t2_image", "optional": true, "path-template": "[T2]_preprocessed.nrrd", "path-template-stripped-extensions": [".nii.gz", ".nii"], "name": "Preprocessed T2 image"}], "suggestedresources": {"walltime-estimate": 1200}, "name": "animaMSExamPreparation", "ark_id": "https://n2t.net/ark:/70798/p763prw6q0sgm3cx0t", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3384927", "title": "animaMusicLesionSegmentation_v3", "description": "Compute MS lesion segmentation using a cascaded CNN. Uses preprocessed images from animaMSExamRegistration.", "publicationdate": "2019-09-03", "deprecated": false, "downloads": 2841, "author": "Francesca Galassi", "version": "v0.1.2", "doi": "10.5281/zenodo.3384927", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "multiple-sclerosis", "segmentation"]}, "inputs": [{"command-line-flag": "-f", "description": "Path to the MS patient FLAIR image", "value-key": "[FLAIR]", "optional": false, "type": "File", "id": "flair", "name": "flair"}, {"command-line-flag": "-t", "description": "Path to the MS patient T1 image", "value-key": "[T1]", "optional": false, "type": "File", "id": "t1", "name": "t1"}, {"command-line-flag": "-m", "description": "Path to the MS patient brain mask image", "value-key": "[MASKIMAGE]", "optional": false, "type": "File", "id": "maskImage", "name": "maskImage"}, {"command-line-flag": "-o", "description": "Path to output folder", "value-key": "[OUTPUTFOLDER]", "optional": false, "type": "String", "id": "outputFolder", "name": "outputFolder"}, {"command-line-flag": "-n", "description": "Number of execution threads (default: 0 = all cores)", "value-key": "[NBTHREADS]", "optional": true, "type": "Number", "id": "nbThreads", "name": "nbThreads"}], "commandline": "cd /music/music_v3.2/ && python3 /music/music_v3.2/animaMusicLesionSegmentation_v3.py [FLAIR] [T1] [MASKIMAGE] [OUTPUTFOLDER] [NBTHREADS]", "toolversion": "v0.1.2", "containerimage": {"index": "index.docker.io", "image": "arthursw/anima-ms:v1", "type": "docker"}, "outputfiles": [{"path-template": "t1_flair_1608_ce_noNorm_upsampleAnima_rev1/t1_flair_1608_ce_noNorm_upsampleAnima_rev1_prob_1.nii.gz", "optional": false, "description": "Prob image file", "name": "Prob image", "id": "prob_image"}, {"path-template": "t1_flair_1608_ce_noNorm_upsampleAnima_rev1/t1_flair_1608_ce_noNorm_upsampleAnima_rev1_segm.nii.gz", "optional": false, "description": "Segm image file", "name": "Segm image", "id": "segm_image"}], "suggestedresources": {"walltime-estimate": 1200}, "name": "animaMusicLesionSegmentation_v3", "ark_id": "https://n2t.net/ark:/70798/p7hrm287b2f6b8kssw", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3699595", "title": "Dipy Tracking and Connectome Generation", "description": "Pipeline for generating streamlines and creating connectomes from preprocessed diffusion images using Dipy. This tool is the boilerplate tractography provided within Dipy.", "publicationdate": "2020-03-06", "deprecated": false, "downloads": 2134, "author": "Greg Kiar <gkiar.github.io>", "version": "v0.4.0", "doi": "10.5281/zenodo.3699595", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "image processing", "mri", "connectome", "diffusion", "fuzzy"]}, "commandline": "python3.6 /opt/dipy_tracking.py [DIFFUSION_IMAGE] [BVECS] [BVALS] [WHITEMATTER_MASK] [SEED_MASK] [OUTPUT_DIRECTORY] [LABELS] [VERBOSE] [PROB] [PRUNE] [RANDOM_SEED] [STREAMLINE_PLOT] [BOUTIQUES]", "containerimage": {"image": "gkiar/dipy_tracking:v0.4.0", "index": "index.docker.io", "type": "docker"}, "environmentvariables": [{"description": "The back-end and virtual precision used for the floating point operations. 'libinterflop_mca.so -m rr' is the default ", "name": "VFC_BACKENDS", "value": "[VFC_BACKENDS]"}], "inputs": [{"description": "Image containing a stack of DWI volumes, ideally preprocessed, to be used for tracing. If this is a nifti image, the image is used directly. If it is a JSON file, it is expected to be an output from the 'oneVoxel' noise-simulation tool and the image will be regenerated using the parameters contained in the JSON file.", "id": "diffusion_image", "name": "diffusion_image", "optional": false, "type": "File", "value-key": "[DIFFUSION_IMAGE]"}, {"description": "The b-vectors corresponding to the diffusion images. If the images have been preprocessed then the rotated b-vectors should be used.", "id": "bvecs", "name": "bvecs", "optional": false, "type": "File", "value-key": "[BVECS]"}, {"description": "The b-values corresponding to the diffusion images. ", "id": "bvals", "name": "bvals", "optional": false, "type": "File", "value-key": "[BVALS]"}, {"description": "A white matter mask generated from a structural image that has been transformed into the same space as the diffusion images.", "id": "whitematter_mask", "name": "whitematter_mask", "optional": false, "type": "File", "value-key": "[WHITEMATTER_MASK]"}, {"description": "A seed mask, recommended as the white matter and gray matter boundary. This can be derived from the white matter mask by dilating the image and subtracting the original mask.", "id": "seed_mask", "name": "seed_mask", "optional": false, "type": "File", "value-key": "[SEED_MASK]"}, {"description": "The directory in which the streamlines and optionally graphs and figures will be saved in.", "id": "output_directory", "name": "output_directory", "optional": false, "type": "String", "value-key": "[OUTPUT_DIRECTORY]"}, {"command-line-flag": "--labels", "description": "Optional nifti image containing co-registered region labels pertaining to a parcellation. This file will be used for generating a connectome from the streamlines.", "id": "labels", "list": true, "name": "labels", "optional": true, "type": "File", "value-key": "[LABELS]"}, {"command-line-flag": "--verbose", "description": "Toggles verbose or quiet output printing.", "id": "verbose", "name": "verbose", "optional": true, "type": "Flag", "value-key": "[VERBOSE]"}, {"command-line-flag": "--prob", "description": "Toggles probabilistic tracking. Deterministic tracking is used if unspecified.", "id": "prob", "name": "prob", "optional": true, "type": "Flag", "value-key": "[PROB]"}, {"command-line-flag": "--prune", "default-value": 3, "description": "Dictates the minimum length of fibers to keep. If fibers are shorter than the value, exclusive,then they will be thrown out. Default value is 3 nodes in the fiber.", "id": "prune", "integer": true, "minimum": 0, "name": "prune", "optional": true, "type": "Number", "value-key": "[PRUNE]"}, {"command-line-flag": "--random_seed", "default-value": 42, "description": "Random seed to be used in tractography.", "id": "random_seed", "integer": true, "minimum": 0, "name": "random_seed", "optional": true, "type": "Number", "value-key": "[RANDOM_SEED]"}, {"command-line-flag": "--streamline_plot", "description": "Toggles the plotting of streamlines. This requires VTK.", "id": "streamline_plot", "name": "streamline_plot", "optional": true, "type": "Flag", "value-key": "[STREAMLINE_PLOT]"}, {"command-line-flag": "--boutiques", "description": "Toggles creation of a Boutiques descriptor and invocation from the tool and inputs.", "id": "boutiques", "name": "boutiques", "optional": true, "type": "Flag", "value-key": "[BOUTIQUES]"}, {"default-value": "libinterflop_mca.so -m rr", "id": "VFC_BACKENDS", "name": "VFC Backends", "optional": true, "type": "File", "value-key": "[VFC_BACKENDS]"}], "name": "Dipy Tracking and Connectome Generation", "outputfiles": [{"conditional-path-template": [{"prob": "[OUTPUT_DIRECTORY]/*/*/dwi/[DIFFUSION_IMAGE]_prob_rs[RANDOM_SEED].trk"}, {"default": "[OUTPUT_DIRECTORY]/*/*/dwi/[DIFFUSION_IMAGE]_det_rs[RANDOM_SEED].trk"}], "id": "fibers", "name": "Fibers", "optional": false, "path-template-stripped-extensions": [".nii.gz", ".nii", ".json"]}, {"conditional-path-template": [{"prob": "[OUTPUT_DIRECTORY]/*/*/dwi/[DIFFUSION_IMAGE]_prob_rs[RANDOM_SEED].png"}, {"default": "[OUTPUT_DIRECTORY]/*/*/dwi/[DIFFUSION_IMAGE]_det_rs[RANDOM_SEED].png"}], "id": "fibers_plot", "name": "Fibers Plot", "optional": true, "path-template-stripped-extensions": [".nii.gz", ".nii", ".json"]}, {"conditional-path-template": [{"prob": "[OUTPUT_DIRECTORY]/*/*/dwi/[DIFFUSION_IMAGE]_prob_rs[RANDOM_SEED]_*.mat"}, {"default": "[OUTPUT_DIRECTORY]/*/*/dwi/[DIFFUSION_IMAGE]_det_rs[RANDOM_SEED]_*.mat"}], "id": "graph", "list": true, "name": "Graphs", "optional": true, "path-template-stripped-extensions": [".nii.gz", ".nii", ".json"]}, {"conditional-path-template": [{"prob": "[OUTPUT_DIRECTORY]/*/*/dwi/[DIFFUSION_IMAGE]_prob_rs[RANDOM_SEED]_*.png"}, {"default": "[OUTPUT_DIRECTORY]/*/*/dwi/[DIFFUSION_IMAGE]_det_rs[RANDOM_SEED]_*.png"}], "id": "graph_plot", "list": true, "name": "Graph plots", "optional": true, "path-template-stripped-extensions": [".nii.gz", ".nii", ".json"]}, {"conditional-path-template": [{"prob": "[OUTPUT_DIRECTORY]/*/*/dwi/[DIFFUSION_IMAGE]_prob_rs[RANDOM_SEED]_*_mapping.json"}, {"default": "[OUTPUT_DIRECTORY]/*/*/dwi/[DIFFUSION_IMAGE]_det_rs[RANDOM_SEED]_*_mapping.json"}], "id": "graph_edge_mapping", "list": true, "name": "Graph edge mappings", "optional": true, "path-template-stripped-extensions": [".nii.gz", ".nii", ".json"]}], "suggestedresources": {"cpu-cores": 1, "ram": 4096, "walltime-estimate": 45}, "toolversion": "v0.4.0", "ark_id": "https://n2t.net/ark:/70798/p7h9cnxgd4bks0j1fj", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3736822", "title": "rvtest", "description": "Rvtests, which stands for Rare Variant tests, is a flexible software package for genetic association analysis for sequence datasets. Since its inception, rvtests was developed as a comprehensive tool to support genetic association analysis and meta-analysis. It can analyze both unrelated individual and related (family-based) individuals for both quantitative and binary outcomes. It includes a variety of association tests (e.g. single variant score test, burden test, variable threshold test, SKAT test, fast linear mixed model score test). It takes VCF/BGEN/PLINK format as genotype input file and takes PLINK format phenotype file and covariate file. With new implementation of the BOLT-LMM/MINQUE algorithm as well as a series of software engineering optimizations, our software package is capable of analyzing datasets of up to 1,000,000 individuals in linear mixed models on a computer workstation, which makes our tool one of the very few options for analyzing large biobank scale datasets, such as UK Biobank. RVTESTS supports both single variant and gene-level tests. It also allows for highly effcient generation of covariance matrices between score statistics in RAREMETAL format, which can be used to support the next wave of meta-analysis that incorporates large biobank datasets. A (much) larger sample size can be handled using linear regression or logistic regression models.", "publicationdate": "2020-04-01", "deprecated": false, "downloads": 1918, "author": "Xiaowei Zhan", "version": "2.1.0", "doi": "10.5281/zenodo.3736822", "schemaversion": "0.5", "container": "singularity", "tags": {"genetics": true, "ENIGMA": true}, "name": "rvtest", "descriptorurl": "https://raw.githubusercontent.com/glatard/rvtests-docker/master/rvtests.json", "url": "https://github.com/zhanxw/rvtests", "toolversion": "2.1.0", "commandline": "mkdir -p ./[OUT] ; rvtest [INVCF] [INBGEN] [INBGENSAMPLE] [INKGG] --out ./[OUT]/[OUT] [OUTPUTRAW] [COVAR] [COVARNAME] [SEX] [PHENO] [INVERSENORMAL] [USERESIDUALASPHENOTYPE] [MPHENO] [PHENONAME] [QTL] [MULTIPLEPHENO] [DOSAGE] [MULTIPLEALLELE] [XLABEL] [XPARREGION] [PEOPLEINCLUDEID] [PEOPLEINCLUDEFILE] [PEOPLEEXCLUDEID] [PEOPLEEXCLUDEFILE] [RANGELIST] [RANGEFILE] [SITEFILE] [SITEDEPTHMIN] [SITEDEPTHMAX] [SITEMACMIN] [ANNOTYPE] [INDVDEPTHMIN] [INDVDEPTHMAX] [INDVQUALMIN] [SINGLE] [BURDEN] [VT] [KERNEL] [META] [KINSHIP] [XHEMIKINSHIP] [KINSHIPEIGEN] [XHEMIKINSHIPEIGEN] [BOLTPLINK] [BOLTPLINKNOCHECK] [GENEFILE] [GENE] [SETLIST] [SETFILE] [SET] [FREQUPPER] [FREQLOWER] [IMPUTE] [IMPUTEPHENO] [IMPUTECOV] [CONDITION] [NOWEB] [HIDECOVAR] [NUMTHREAD] [OUTPUTID]", "containerimage": {"image": "glatard/rvtests:2.1.0", "index": "docker://", "type": "singularity"}, "onlineplatformurls": ["https://portal.cbrain.mcgill.ca"], "groups": [{"id": "inputs", "name": "Inputs", "members": ["inVcf", "inBgen", "inKgg"], "one-is-required": true}, {"id": "basic_input_output", "name": "Basic Input/Output", "members": ["inVcf", "inBgen", "inBgenSample", "inKgg", "out", "outputRaw"]}, {"id": "specify_covariate", "name": "Specify Covariate", "members": ["covar", "covarname", "sex"]}, {"id": "specify_phenotype", "name": "Specify Phenotype", "members": ["pheno", "inverseNormal", "useResidualAsPhenotype", "mpheno", "phenoname", "qtl", "multiplePheno"]}, {"id": "specify_genotype", "name": "Specify Genotype", "members": ["dosage", "multipleAllele"]}, {"id": "chromosome_x_options", "name": "Chromosome X Options", "members": ["xLabel", "xParRegion"]}, {"id": "people_filter", "name": "People Filter", "members": ["peopleIncludeID", "peopleIncludeFile", "peopleExcludeID", "peopleExcludeFile"]}, {"id": "site_filter", "name": "Site Filter", "members": ["rangeList", "rangeFile", "siteFile", "siteDepthMin", "siteDepthMax", "siteMACMin", "annoType"]}, {"id": "genotype_filter", "name": "Genotype Filter", "members": ["indvDepthMin", "indvDepthMax", "indvQualMin"]}, {"id": "association_model", "name": "Association Model", "members": ["single", "burden", "vt", "kernel", "meta"]}, {"id": "family_based_models", "name": "Family-based Models", "members": ["kinship", "xHemiKinship", "kinshipEigen", "xHemiKinshipEigen", "boltPlink", "boltPlinkNoCheck"]}, {"id": "grouping_unit", "name": "Grouping Unit", "members": ["geneFile", "gene", "setList", "setFile", "set"]}, {"id": "frequency_cutoff", "name": "Frequency Cutoff", "members": ["freqUpper", "freqLower"]}, {"id": "missing_data", "name": "Missing Data", "members": ["impute", "imputePheno", "imputeCov"]}, {"id": "conditional_analysis", "name": "Conditional Analysis", "members": ["condition"]}, {"id": "auxiliary_functions", "name": "Auxiliary Functions", "members": ["noweb", "hidecovar", "numThread", "outputID"]}], "inputs": [{"id": "inVcf", "name": "inVcf", "command-line-flag": "--inVcf", "type": "File", "value-key": "[INVCF]", "description": "Input VCF File", "optional": true}, {"id": "inBgen", "name": "inBgen", "command-line-flag": "--inBgen", "type": "File", "value-key": "[INBGEN]", "description": "Input BGEN File", "optional": true}, {"id": "inBgenSample", "name": "inBgenSample", "command-line-flag": "--inBgenSample", "type": "String", "value-key": "[INBGENSAMPLE]", "description": "Input Sample IDs for the BGEN File", "requires-inputs": ["inBgen"], "optional": true}, {"id": "inKgg", "name": "inKgg", "command-line-flag": "--inKgg", "type": "File", "value-key": "[INKGG]", "description": "Input KGG File", "optional": true}, {"id": "out", "name": "out", "type": "String", "value-key": "[OUT]", "default-value": "rvtest", "description": "Output prefix"}, {"id": "outputRaw", "name": "outputRaw", "command-line-flag": "--outputRaw", "type": "Flag", "value-key": "[OUTPUTRAW]", "optional": true, "description": "Output genotypes, phenotype, covariates(if any); and collapsed genotype to tabular files"}, {"id": "covar", "name": "covar", "command-line-flag": "--covar", "type": "File", "value-key": "[COVAR]", "optional": true, "description": "Specify covariate file"}, {"id": "covarname", "name": "covar-name", "command-line-flag": "--covar-name", "type": "String", "value-key": "[COVARNAME]", "optional": true, "requires-inputs": ["covar"], "description": "Specify the column names in covariate file to be included in analysis"}, {"id": "sex", "name": "sex", "command-line-flag": "--sex", "type": "Flag", "value-key": "[SEX]", "optional": true, "requires-inputs": ["covar"], "description": "Include sex (5th column in the PED file) as a covariate"}, {"id": "pheno", "name": "pheno", "command-line-flag": "--pheno", "type": "File", "value-key": "[PHENO]", "description": "Specify phenotype file"}, {"id": "inverseNormal", "name": "inverseNormal", "command-line-flag": "--inverseNormal", "type": "Flag", "optional": true, "value-key": "[INVERSENORMAL]", "description": "Transform phenotype like normal distribution"}, {"id": "useResidualAsPhenotype", "name": "useResidualAsPhenotype", "command-line-flag": "--useResidualAsPhenotype", "type": "Flag", "optional": true, "value-key": "[USERESIDUALASPHENOTYPE]", "description": "Fit covariate ~ phenotype, use residual to replace phenotype"}, {"id": "mpheno", "name": "mpheno", "command-line-flag": "--mpheno", "type": "Number", "integer": true, "minimum": 1, "optional": true, "value-key": "[MPHENO]", "description": "Specify which phenotype column to read (default: 1)"}, {"id": "phenoname", "name": "phenoname", "command-line-flag": "--pheno-name", "type": "String", "optional": true, "value-key": "[PHENONAME]", "description": "Specify which phenotype column to read by header"}, {"id": "qtl", "name": "qtl", "command-line-flag": "--qtl", "type": "Flag", "value-key": "[QTL]", "optional": true, "description": "Treat phenotype as quantitative trait"}, {"id": "multiplePheno", "name": "multiplePheno", "command-line-flag": "--multiplePheno", "type": "File", "optional": true, "value-key": "[MULTIPLEPHENO]", "description": "Specify a template file for analyses of more than one phenotype"}, {"id": "dosage", "name": "dosage", "command-line-flag": "--dosage", "type": "String", "value-key": "[DOSAGE]", "optional": true, "description": "Specify which dosage tag to use. (e.g. EC or DS);"}, {"id": "multipleAllele", "name": "multipleAllele", "command-line-flag": "--multipleAllele", "type": "String", "optional": true, "value-key": "[MULTIPLEALLELE]", "description": "Support multi-allelic genotypes"}, {"id": "xLabel", "name": "xLabel", "command-line-flag": "--xLabel", "type": "String", "optional": true, "value-key": "[XLABEL]", "description": "Specify X chromosome label (default: 23|X);"}, {"id": "xParRegion", "name": "xParRegion", "command-line-flag": "--xParRegion", "type": "String", "optional": true, "value-key": "[XPARREGION]", "description": "Specify PAR region (default: hg19);, can be build number e.g. hg38, b37; or specify region, e.g. '60001-2699520,154931044-155260560'"}, {"id": "peopleIncludeID", "name": "peopleIncludeID", "command-line-flag": "--peopleIncludeID", "type": "Number", "optional": true, "list": true, "integer": true, "value-key": "[PEOPLEINCLUDEID]", "description": "List IDs of people that will be included in study"}, {"id": "peopleIncludeFile", "name": "peopleIncludeFile", "command-line-flag": "--peopleIncludeFile", "type": "File", "optional": true, "value-key": "[PEOPLEINCLUDEFILE]", "description": "From given file, set IDs of people that will be"}, {"id": "peopleExcludeID", "name": "peopleExcludeID", "command-line-flag": "--peopleExcludeID", "type": "Number", "integer": true, "list": true, "optional": true, "value-key": "[PEOPLEEXCLUDEID]", "description": "List IDs of people that will be excluded from study"}, {"id": "peopleExcludeFile", "name": "peopleExcludeFile", "command-line-flag": "--peopleExcludeFile", "type": "File", "value-key": "[PEOPLEEXCLUDEFILE]", "optional": true, "description": "From given file, set IDs of people that will be excluded from study"}, {"id": "rangeList", "name": "rangeList", "command-line-flag": "--rangeList", "type": "File", "list": true, "optional": true, "value-key": "[RANGELIST]", "description": "Specify some ranges to use, please use chr:begin-end format."}, {"id": "rangeFile", "name": "rangeFile", "command-line-flag": "--rangeFile", "type": "File", "optional": true, "value-key": "[RANGEFILE]", "description": "Specify the file containing ranges, please use chr:begin-end format."}, {"id": "siteFile", "name": "siteFile", "command-line-flag": "--siteFile", "type": "File", "optional": true, "value-key": "[SITEFILE]", "description": "Specify the file containing sites to include, please use \"chr pos\" format."}, {"id": "siteDepthMin", "name": "siteDepthMin", "command-line-flag": "--siteDepthMin", "type": "Number", "optional": true, "value-key": "[SITEDEPTHMIN]", "description": "Specify minimum depth(inclusive); to be included in analysis"}, {"id": "siteDepthMax", "name": "siteDepthMax", "command-line-flag": "--siteDepthMax", "type": "Number", "optional": true, "value-key": "[SITEDEPTHMAX]", "description": "Specify maximum depth(inclusive); to be included in analysis"}, {"id": "siteMACMin", "name": "siteMACMin", "command-line-flag": "--siteMACMin", "type": "Number", "integer": true, "optional": true, "value-key": "[SITEMACMIN]", "description": "Specify minimum Minor Allele Count(inclusive); to be included in analysis"}, {"id": "annoType", "name": "annoType", "command-line-flag": "--annoType", "type": "String", "optional": true, "value-key": "[ANNOTYPE]", "description": "Specify annotation type that is followed by ANNO= in the VCF INFO field, regular expression is allowed"}, {"id": "indvDepthMin", "name": "indvDepthMin", "command-line-flag": "--indvDepthMin", "type": "Number", "optional": true, "value-key": "[INDVDEPTHMIN]", "description": "Specify minimum depth(inclusive); of a sample to be included in analysis"}, {"id": "indvDepthMax", "name": "indvDepthMax", "command-line-flag": "--indvDepthMax", "type": "Number", "optional": true, "value-key": "[INDVDEPTHMAX]", "description": "Specify maximum depth(inclusive); of a sample to be included in the analysis"}, {"id": "indvQualMin", "name": "indvQualMin", "command-line-flag": "--indvQualMin", "type": "Number", "optional": true, "value-key": "[INDVQUALMIN]", "description": "Specify minimum depth(inclusive); of a sample to be included in the analysis"}, {"id": "single", "name": "single", "command-line-flag": "--single", "type": "String", "optional": true, "value-key": "[SINGLE]", "description": "Single variant tests, choose from: score, wald, exact, famScore, famLrt, famGrammarGamma, firth", "value-choices": ["score", "wald", "exact", "famScore", "famLrt", "famGrammarGamma", "firth"]}, {"id": "burden", "name": "burden", "command-line-flag": "--burden", "type": "String", "optional": true, "value-key": "[BURDEN]", "description": "Burden tests, choose from: cmc, zeggini, mb, exactCMC, rarecover, cmat, cmcWald", "value-choices": ["cmc", "zeggini", "mb", "exactCMC", "rarecover", "cmat", "cmcWald"]}, {"id": "vt", "name": "vt", "command-line-flag": "--vt", "type": "String", "optional": true, "value-key": "[VT]", "description": "Variable threshold tests, choose from: price, analytic", "value-choices": ["price", "analytic"]}, {"id": "kernel", "name": "kernel", "command-line-flag": "--kernel", "type": "String", "optional": true, "value-key": "[KERNEL]", "description": "Kernal-based tests, choose from: SKAT, KBAC, FamSKAT, SKATO", "value-choices": ["SKAT", "KBAC", "FamSKAT", "SKATO"]}, {"id": "meta", "name": "meta", "command-line-flag": "--meta", "type": "String", "value-key": "[META]", "list": true, "list-separator": ",", "optional": true, "description": "Meta-analysis related functions to generate summary statistics, choose from: score, cov, dominant, recessive", "value-choices": ["score", "cov", "dominant", "recessive"]}, {"id": "kinship", "name": "kinship", "command-line-flag": "--kinship", "type": "File", "value-key": "[KINSHIP]", "optional": true, "description": "Specify a kinship file for autosomal analysis, use vcf2kinship to generate"}, {"id": "xHemiKinship", "name": "xHemiKinship", "command-line-flag": "--xHemiKinship", "type": "String", "value-key": "[XHEMIKINSHIP]", "optional": true, "description": "Provide kinship for the chromosome X hemizygote region"}, {"id": "kinshipEigen", "name": "kinshipEigen", "command-line-flag": "--kinshipEigen", "type": "File", "value-key": "[KINSHIPEIGEN]", "optional": true, "description": "Specify eigen decomposition results of a kinship file for X analysis"}, {"id": "xHemiKinshipEigen", "name": "xHemiKinshipEigen", "command-line-flag": "--xHemiKinshipEigen", "type": "File", "value-key": "[XHEMIKINSHIPEIGEN]", "optional": true, "description": "Specify eigen decomposition results of a kinship file for X analysis"}, {"id": "boltPlink", "name": "boltPlink", "command-line-flag": "--boltPlink", "type": "String", "value-key": "[BOLTPLINK]", "optional": true, "description": "Specify a prefix of binary PLINK inputs for BoltLMM"}, {"id": "boltPlinkNoCheck", "name": "boltPlinkNoCheck", "command-line-flag": "--boltPlinkNoCheck", "type": "Flag", "optional": true, "value-key": "[BOLTPLINKNOCHECK]", "description": "Not checking MAF and missingness for binary PLINK file"}, {"id": "geneFile", "name": "geneFile", "command-line-flag": "--geneFile", "type": "File", "value-key": "[GENEFILE]", "optional": true, "description": "Specify a gene file (for burden tests);"}, {"id": "gene", "name": "gene", "command-line-flag": "--gene", "type": "String", "value-key": "[GENE]", "optional": true, "description": "Specify which genes to test"}, {"id": "setList", "name": "setList", "command-line-flag": "--setList", "type": "String", "list": true, "optional": true, "value-key": "[SETLIST]", "description": "Specify a list to test (for burden tests);"}, {"id": "setFile", "name": "setFile", "command-line-flag": "--setFile", "type": "File", "optional": true, "value-key": "[SETFILE]", "description": "Specify a list file (for burden tests, first 2 columns: setName chr:beg-end);"}, {"id": "set", "name": "set", "command-line-flag": "--set", "type": "String", "optional": true, "value-key": "[SET]", "description": "Specify which set to test (1st column);"}, {"id": "freqUpper", "name": "freqUpper", "command-line-flag": "--freqUpper", "type": "Number", "optional": true, "value-key": "[FREQUPPER]", "description": "Specify upper minor allele frequency bound to be included in analysis"}, {"id": "freqLower", "name": "freqLower", "command-line-flag": "--freqLower", "type": "Number", "optional": true, "value-key": "[FREQLOWER]", "description": "Specify lower minor allele frequency bound to be included in analysis"}, {"id": "impute", "name": "impute", "command-line-flag": "--impute", "type": "String", "value-key": "[IMPUTE]", "optional": true, "value-choices": ["mean", "hwe", "drop"], "description": "Impute missing genotype (default:mean):  mean, hwe, and drop"}, {"id": "imputePheno", "name": "imputePheno", "command-line-flag": "--imputePheno", "type": "Flag", "optional": true, "value-key": "[IMPUTEPHENO]", "description": "Impute phenotype to mean of those have genotypes but no phenotypes"}, {"id": "imputeCov", "name": "imputeCov", "command-line-flag": "--imputeCov", "type": "Flag", "optional": true, "value-key": "[IMPUTECOV]", "description": "Impute each covariate to its mean, instead of drop samples with missing covariates"}, {"id": "condition", "name": "condition", "command-line-flag": "--condition", "type": "String", "list": true, "optional": true, "value-key": "[CONDITION]", "description": "Specify markers to be conditions (specify range);"}, {"id": "noweb", "name": "noweb", "command-line-flag": "--noweb", "type": "Flag", "value-key": "[NOWEB]", "optional": true, "description": "Skip checking new version"}, {"id": "hidecovar", "name": "hidecovar", "command-line-flag": "--hide-covar", "type": "Flag", "optional": true, "value-key": "[HIDECOVAR]", "description": "Surpress output lines of covariates"}, {"id": "numThread", "name": "numThread", "command-line-flag": "--numThread", "type": "Number", "integer": true, "minimum": 1, "optional": true, "value-key": "[NUMTHREAD]", "description": "Specify number of threads (default:1)"}, {"id": "outputID", "name": "outputID", "command-line-flag": "--outputID", "type": "Flag", "optional": true, "value-key": "[OUTPUTID]", "description": "Output VCF IDs in single-variant association results"}], "outputfiles": [{"id": "output_dir", "name": "Output directory", "optional": false, "path-template": "[OUT]"}], "tests": [{"name": "test1", "invocation": {"pheno": "/usr/share/example/pheno", "inVcf": "/usr/share/example/example.vcf", "single": "wald", "out": "out1"}, "assertions": {"exit-code": 0}}, {"name": "test2", "invocation": {"pheno": "/usr/share/example/pheno", "inVcf": "/usr/share/example/example.vcf", "mpheno": 2, "single": "wald", "out": "out2"}, "assertions": {"exit-code": 0}}, {"name": "test3", "invocation": {"pheno": "/usr/share/example/pheno", "inVcf": "/usr/share/example/example.vcf", "phenoname": "y2", "single": "wald", "out": "out3"}, "assertions": {"exit-code": 0}}, {"name": "test4", "invocation": {"pheno": "/usr/share/example/pheno", "inVcf": "/usr/share/example/example.vcf", "covar": "/usr/share/example/covar", "covarname": "c1,c2", "single": "wald", "out": "out4"}, "assertions": {"exit-code": 0}}, {"name": "test5", "invocation": {"pheno": "/usr/share/example/pheno", "inVcf": "/usr/share/example/example.vcf", "covar": "/usr/share/example/covar.missing", "covarname": "c1,c2", "single": "wald", "out": "out5"}, "assertions": {"exit-code": 0}}, {"name": "test6", "invocation": {"pheno": "/usr/share/example/pheno", "inVcf": "/usr/share/example/example.vcf", "meta": ["score", "cov"], "covar": "/usr/share/example/covar", "covarname": "c1,c2", "useResidualAsPhenotype": true, "inverseNormal": true, "single": "wald", "out": "out6"}, "assertions": {"exit-code": 0}}], "suggestedresources": {"walltime-estimate": 3600}, "ark_id": "https://n2t.net/ark:/70798/p7f05qxx74j6n6qpt1", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3873808", "title": "spark parallel (stage 3 of 3)", "description": "SParsity-based Analysis of Reliable K-hubness (SPARK) for brain fMRI functional connectivity", "publicationdate": "2020-06-03", "deprecated": false, "downloads": 1521, "author": "Multi FunkIm", "version": "v1.2.1", "doi": "10.5281/zenodo.3873808", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "fmri", "neuroimaging"]}, "name": "spark parallel (stage 3 of 3)", "commandline": "spark --RUN --stage C [FMRI] [OUT_DIR] [VERBOSE] && spark --WRAP-UP [FMRI] [OUT_DIR] [MOVE-OUTPUTS] [VERBOSE]", "containerimage": {"image": "multifunkim/spark-matlab", "type": "docker"}, "inputs": [{"command-line-flag": "--fmri", "description": "Path (absolute or relative) to the fMRI data to analyze. Notes: - This file should be a valid fMRI file of a BIDS dataset. - The filename will be used to name the outputs, for example: 'kmap_sub-01_task-rest_bold.mat'.", "id": "fmri", "name": "fMRI data", "optional": false, "type": "File", "value-key": "[FMRI]"}, {"command-line-flag": "--out-dir", "description": "Path (absolute or relative) to the output directory (old files might get replaced). By default, a new directory named after the specified input --fmri is created relative this output directory --out-dir to avoid conflicts. To change this default setting, use --move-outputs (useful to merge results of multiple analyses).", "id": "out_dir", "name": "Output directory name", "optional": false, "type": "File", "value-key": "[OUT_DIR]"}, {"command-line-flag": "--verbose", "description": "If set, the program will provide some additional details.", "id": "verbose", "name": "Verbose", "optional": true, "type": "Flag", "value-key": "[VERBOSE]"}, {"command-line-flag": "--move-outputs", "description": "If set, all outputs for this analysis will be moved to the specified output directory --out-dir. This flag is useful to merge in a single directory the results of different analyses where the input fMRI were different.", "id": "move_outputs", "name": "Move output files", "optional": true, "type": "Flag", "value-key": "[MOVE-OUTPUTS]"}], "outputfiles": [{"description": "Results directory containing:  k-hubness maps, atom maps and intermediate files. (file formats: MINC, NIfTI)", "id": "result", "name": "Results directory", "optional": false, "path-template": "[OUT_DIR]"}], "suggestedresources": {"cpu-cores": 2, "ram": 12, "walltime-estimate": 100000}, "toolversion": "v1.2.1", "ark_id": "https://n2t.net/ark:/70798/p7ckjwb614nn92vg5f", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3873817", "title": "spark parallel (stage 2 of 3)", "description": "SParsity-based Analysis of Reliable K-hubness (SPARK) for brain fMRI functional connectivity", "publicationdate": "2020-06-03", "deprecated": false, "downloads": 1515, "author": "Multi FunkIm", "version": "v1.2.1", "doi": "10.5281/zenodo.3873817", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "fmri", "neuroimaging"]}, "name": "spark parallel (stage 2 of 3)", "descriptorurl": "https://github.com/multifunkim/spark-cbrain", "commandline": "spark --RUN --stage B [FMRI] [OUT_DIR] [VERBOSE] boot[JOBS-PATTERNS]_", "containerimage": {"image": "multifunkim/spark-matlab", "type": "docker"}, "inputs": [{"command-line-flag": "--fmri", "description": "Path (absolute or relative) to the fMRI data to analyze. Notes: - This file should be a valid fMRI file of a BIDS dataset. - The filename will be used to name the outputs, for example: 'kmap_sub-01_task-rest_bold.mat'.", "id": "fmri", "name": "fMRI data", "optional": false, "type": "File", "value-key": "[FMRI]"}, {"command-line-flag": "--out-dir", "description": "Path (absolute or relative) to the output directory (old files might get replaced). By default, a new directory named after the specified input --fmri is created relative this output directory --out-dir to avoid conflicts. To change this default setting, use --move-outputs (useful to merge results of multiple analyses).", "id": "out_dir", "name": "Output directory name", "optional": false, "type": "File", "value-key": "[OUT_DIR]"}, {"command-line-flag": "--verbose", "description": "If set, the program will provide some additional details.", "id": "verbose", "name": "Verbose", "optional": true, "type": "Flag", "value-key": "[VERBOSE]"}, {"description": "Job number to run. Must be lower or equal to nb_resamplings used during setup.", "id": "jobs_patterns", "name": "Jobs patterns", "optional": false, "type": "Number", "integer": true, "maximum": 100, "value-key": "[JOBS-PATTERNS]"}], "outputfiles": [{"description": "Results directory containing:  k-hubness maps, atom maps and intermediate files. (file formats: MINC, NIfTI)", "id": "result", "name": "Results directory", "optional": false, "path-template": "[OUT_DIR]"}], "suggestedresources": {"cpu-cores": 2, "ram": 12, "walltime-estimate": 100000}, "toolversion": "v1.2.1", "ark_id": "https://n2t.net/ark:/70798/p7k5h73j55d6z2mstb", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3873816", "title": "spark parallel (stage 1 of 3)", "description": "SParsity-based Analysis of Reliable K-hubness (SPARK) for brain fMRI functional connectivity", "publicationdate": "2020-06-03", "deprecated": false, "downloads": 1500, "author": "Multi FunkIm", "version": "v1.2.1", "doi": "10.5281/zenodo.3873816", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "fmri", "neuroimaging"]}, "name": "spark parallel (stage 1 of 3)", "descriptorurl": "https://github.com/multifunkim/spark-cbrain", "commandline": "spark --SETUP [FMRI] [OUT_DIR] [MASK] [NB_RESAMPLINGS] [NETWORK_SCALES] [NB_ITERATIONS] [P_VALUE] [RESAMPLING_METHOD] [BLOCK_WINDOW_LENGTH] [DICT_INIT_METHOD] [SPARSE_CODING_METHOD] [PRESERVE_DC_ATOM] [VERBOSE] && spark --RUN --stage A [FMRI] [OUT_DIR] [VERBOSE]", "containerimage": {"image": "multifunkim/spark-matlab", "type": "docker"}, "groups": [{"id": "bootstrap_resampling", "members": ["nb_resamplings", "resampling_method", "block_window_length"], "name": "Bootstrap resampling"}, {"id": "sparse_dict_learning", "members": ["network_scales", "nb_iterations", "dict_init_method", "sparse_coding_method", "preserve_dc_atom"], "name": "Sparse dictionary learning"}, {"id": "k_hubness_map_generation", "members": ["p_value"], "name": "k-hubness map generation"}], "inputs": [{"command-line-flag": "--fmri", "description": "Path (absolute or relative) to the fMRI data to analyze. Notes: - This file should be a valid fMRI file of a BIDS dataset. - The filename will be used to name the outputs, for example: 'kmap_sub-01_task-rest_bold.mat'.", "id": "fmri", "name": "fMRI data", "optional": false, "type": "File", "value-key": "[FMRI]"}, {"command-line-flag": "--out-dir", "description": "Path (absolute or relative) to the output directory (old files might get replaced). By default, a new directory named after the specified input --fmri is created relative this output directory --out-dir to avoid conflicts. To change this default setting, use --move-outputs (useful to merge results of multiple analyses).", "id": "out_dir", "name": "Output directory name", "optional": false, "type": "String", "value-key": "[OUT_DIR]"}, {"command-line-flag": "--mask", "description": "Path (absolute or relative) to the grey-matter mask. (file formats: MINC, NIfTI)", "id": "mask", "name": "Grey-matter mask", "optional": false, "type": "File", "value-key": "[MASK]"}, {"command-line-flag": "--nb-resamplings", "description": "Number of bootstrap resamplings at the individual level. (recommended: 100)", "default-value": 100, "id": "nb_resamplings", "integer": true, "minimum": 2, "name": "Number of resamplings", "optional": false, "type": "Number", "value-key": "[NB_RESAMPLINGS]"}, {"command-line-flag": "--network-scales", "description": "Three integers, respectively: [begin] [step] [end], used to create a regularly-spaced vector. In order to specify a single number, for instance '12', enter the same number for [begin] and [end], as: '--network-scales 12 1 12'. The numbers in the vector correspond to the range of network scales to be tested. An optimal network scale will be automatically estimated from the vector. (recommended: 10 2 30)", "default-value": [10, 2, 30], "id": "network_scales", "integer": true, "list": true, "max-list-entries": 3, "min-list-entries": 3, "minimum": 1, "name": "Network scales", "optional": false, "type": "Number", "value-key": "[NETWORK_SCALES]"}, {"command-line-flag": "--nb-iterations", "description": "Number of iterations for the sparse dictionary learning.  (recommended: 20)", "default-value": 20, "id": "nb_iterations", "integer": true, "minimum": 2, "name": "Number of iterations", "optional": false, "type": "Number", "value-key": "[NB_ITERATIONS]"}, {"command-line-flag": "--p-value", "default-value": 0.05, "description": "Significance level, using a Z-test, for removing inconsistent elements in the average sparse coefficients (considered as Gaussian noise) after spatial clustering.", "id": "p_value", "maximum": 1, "minimum": 0, "name": "P-Value", "optional": false, "type": "Number", "value-key": "[P_VALUE]"}, {"command-line-flag": "--resampling-method", "default-value": "CBB", "description": "Method (from NIAK) used to resample the data under the null hypothesis. Note: If 'CBB' is selected, the option --block-window-length is used. - CBB: Circular-block-bootstrap sample of multiple time series. - AR1B: Bootstrap sample of multiple time series based on a semiparametric scheme mixing an auto-regressive temporal model and i.i.d. bootstrap of the 'innovations'. - AR1G: Bootstrap sample of multiple time series based on a parametric model of Gaussian data with arbitrary spatial correlations and first-order auto-regressive temporal correlations.", "id": "resampling_method", "name": "Resampling method", "optional": true, "type": "String", "value-choices": ["CBB", "AR1B", "AR1G"], "value-disables": {"AR1B": ["block_window_length"], "AR1G": ["block_window_length"], "CBB": []}, "value-key": "[RESAMPLING_METHOD]", "value-requires": {"AR1B": [], "AR1G": [], "CBB": ["block_window_length"]}}, {"command-line-flag": "--block-window-length", "default-value": [10, 1, 30], "description": "Three numbers, respectively: [begin] [step] [end], used to create a regularly-spaced vector. In order to specify a single number, for instance '12', enter the same number for [begin] and [end], as: '--block-window-length 12 1 12'. A number in the vector corresponds to a window length used in the circular block bootstrap. The unit of the window length is \u2018time-point\u2019 with each time-point indicating a 3D scan at each TR. If the vector contains multiple numbers, then a number will be randomly selected from it at each resampling. It is recommended to use window lengths greater or equal to sqrt(T), where T is the total number of time points in the fMRI time-course. It is also recommended to randomize the window length used at each resampling to reduce a bias by window size.", "id": "block_window_length", "integer": true, "list": true, "max-list-entries": 3, "min-list-entries": 3, "minimum": 1, "name": "Block window length", "optional": true, "type": "Number", "value-key": "[BLOCK_WINDOW_LENGTH]"}, {"command-line-flag": "--dict-init-method", "default-value": "GivenMatrix", "description": "If 'GivenMatrix' is selected, then the dictionary will be initialized by a random permutation of the raw data obtained in step 1. If 'DataElements' is selected, then the dictionary will be initialized by the first N (number of atoms) columns in the raw data obtained in step 1.", "id": "dict_init_method", "name": "Dictionary initialization method", "optional": true, "type": "String", "value-choices": ["GivenMatrix", "DataElements"], "value-key": "[DICT_INIT_METHOD]"}, {"command-line-flag": "--sparse-coding-method", "default-value": "Thresholding", "description": "Sparse coding method for the sparse dictionary learning.", "id": "sparse_coding_method", "name": "Sparse coding method", "optional": true, "type": "String", "value-choices": ["OMP", "Thresholding"], "value-key": "[SPARSE_CODING_METHOD]"}, {"command-line-flag": "--preserve-dc-atom", "description": "If set, then the first atom will be set to a constant and will never change, while all the other atoms will be trained and updated.", "id": "preserve_dc_atom", "name": "Perserve DC atom", "optional": true, "type": "Flag", "value-key": "[PRESERVE_DC_ATOM]"}, {"command-line-flag": "--verbose", "description": "If set, the program will provide some additional details.", "id": "verbose", "name": "Verbose", "optional": true, "type": "Flag", "value-key": "[VERBOSE]"}], "outputfiles": [{"description": "Results directory containing:  k-hubness maps, atom maps and intermediate files. (file formats: MINC, NIfTI)", "id": "result", "name": "Results directory", "optional": false, "path-template": "[OUT_DIR]"}], "suggestedresources": {"cpu-cores": 2, "ram": 12, "walltime-estimate": 100000}, "toolversion": "v1.2.1", "ark_id": "https://n2t.net/ark:/70798/p75m52zpm3zk16029d", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.3899496", "title": "fsl_anat", "description": "General pipeline for processing anatomical images (e.g. T1-weighted scans) via FSL tools. The stages include reorienting the images to the standard (MNI) orientation [fslreorient2std], automatically cropping the image [robustfov], bias-field correction (RF/B1-inhomogeneity-correction) [FAST], registration to standard space (linear and non-linear) [FLIRT and FNIRT], brain-extraction [FNIRT-based or BET], tissue-type segmentation [FAST], and subcortical structure segmentation [FIRST]", "publicationdate": "2020-06-17", "deprecated": false, "downloads": 1362, "author": "Oxford Centre for Functional MRI of the Brain (FMRIB)", "version": "5.0.0", "doi": "10.5281/zenodo.3899496", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "mri"], "toolbox": "fsl"}, "toolversion": "5.0.0", "name": "fsl_anat", "commandline": "fsl_anat [INPUT_FILE] [INPUT_DIR] [OUTPUT_DIR] [CLOBBER_FLAG] [WEAKBIAS_FLAG] [NO_REORIENT_FLAG] [NO_CROP_FLAG] [NO_BIAS_FLAG] [NO_REGISTRATION_FLAG] [NO_NONLINEAR_REG_FLAG] [NO_SEG_FLAG] [NO_SUBCORTSEG_FLAG] [NO_SEARCH_FLAG] [NO_CLEANUP_FLAG] [BIAS_FIELD_SMOOTHING_VAL] [IMAGE_TYPE] [BET_F_PARAM]", "containerimage": {"image": "mcin/docker-fsl:latest", "index": "index.docker.io", "type": "docker"}, "inputs": [{"command-line-flag": "-i", "description": "Input image file (for single-image use), such as .nii.gz. Either this or an input dir (-d) must be specified, but not both.", "value-key": "[INPUT_FILE]", "type": "File", "list": false, "optional": true, "id": "infile", "name": "Input file"}, {"command-line-flag": "-d", "description": "Existing input directory (.anat extension) where this script will be run in place. Either this or an input file (-i) must be specified, but not both.", "value-key": "[INPUT_DIR]", "type": "File", "list": false, "optional": true, "id": "indir", "name": "Input Dir"}, {"command-line-flag": "-o", "description": "Specifies the output folder name. Note that the .anat extension is automatically appended.", "default-value": "output_results", "value-key": "[OUTPUT_DIR]", "type": "String", "list": false, "optional": false, "id": "outdir", "name": "Output directory"}, {"command-line-flag": "--clobber", "description": "If .anat directory exist (as specified by -o or default from -i) then delete it and make a new one.", "value-key": "[CLOBBER_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "clobber_flag", "name": "Clobber flag"}, {"command-line-flag": "--weakbias", "description": "Used for images with little and/or smooth bias fields. For images acquired using birdcage coils or on 1.5T scanners, the --weakbias option will be faster and may produce equally good results.", "value-key": "[WEAKBIAS_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "weak_bias", "name": "Weak bias flag"}, {"command-line-flag": "--noreorient", "description": "Turn off step that does reorientation 2 standard (fslreorient2std).", "value-key": "[NO_REORIENT_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_reorient_flag", "name": "No reorienation flag"}, {"command-line-flag": "--nocrop", "description": "Turn off step that does automated cropping (robustfov).", "value-key": "[NO_CROP_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_crop_flag", "name": "No automated cropping flag"}, {"command-line-flag": "--nobias", "description": "Turn off steps that do bias field correction (via FAST).", "value-key": "[NO_BIAS_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_bias_flag", "name": "No bias field correction flag"}, {"command-line-flag": "--noreg", "description": "Turn off steps that do registration to standard (FLIRT and FNIRT).", "value-key": "[NO_REGISTRATION_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_reg_flag", "name": "No registration flag"}, {"command-line-flag": "--nononlinreg", "description": "Turn off step that does non-linear registration (FNIRT).", "value-key": "[NO_NONLINEAR_REG_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_nonlin_reg_flag", "name": "No non-linear registration flag"}, {"command-line-flag": "--noseg", "description": "Turn off step that does tissue-type segmentation (FAST).", "value-key": "[NO_SEG_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_seg_flag", "name": "No tissue-type segmentation flag"}, {"command-line-flag": "--nosubcortseg", "description": "Turn off step that does sub-cortical segmentation (FIRST).", "value-key": "[NO_SUBCORTSEG_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_subcort_seg_flag", "name": "No subcortical segmentation flag"}, {"command-line-flag": "--nosearch", "description": "Specify that linear registration uses the -nosearch option (FLIRT).", "value-key": "[NO_SEARCH_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_search_flag", "name": "No search in linear registration flag"}, {"command-line-flag": "--nocleanup", "description": "Do not remove intermediate files.", "value-key": "[NO_CLEANUP_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_cleanup_flag", "name": "No cleanup flag"}, {"command-line-flag": "-s", "description": "Specify the value for bias field smoothing (the -l option in FAST).", "value-key": "[BIAS_FIELD_SMOOTHING_VAL]", "type": "Number", "list": false, "optional": true, "id": "bias_field_smoothing_val", "name": "Bias field smoothing value"}, {"command-line-flag": "-t", "description": "Specify the type of image (choose one of T1 T2 PD - default is T1).", "value-key": "[IMAGE_TYPE]", "type": "String", "list": false, "value-choices": ["T1", "T2", "PD"], "optional": true, "id": "image_type", "name": "Image type"}, {"command-line-flag": "--betfparam", "description": "specify the f parameter for BET (only used if not running non-linear reg and also wanting brain extraction done).", "value-key": "[BET_F_PARAM]", "type": "Number", "list": false, "requires-inputs": ["no_nonlin_reg_flag"], "maximum": 1, "minimum": 0, "command-line-flag-separator": "=", "optional": true, "id": "bet_f_param", "name": "F-parameter value for BET"}], "groups": [{"description": "Either a single structural image file (e.g. .nii.gz) or directory (.anat extension) may be given as input", "one-is-required": true, "mutually-exclusive": true, "members": ["infile", "indir"], "id": "group_1", "name": "Input Data"}, {"description": "Parameters for controlling the execution of the fsl_anat task", "id": "group_2", "members": ["clobber_flag", "weak_bias", "no_reorient_flag", "no_crop_flag", "no_bias_flag", "no_reg_flag", "no_nonlin_reg_flag", "no_seg_flag", "no_subcort_seg_flag", "no_search_flag", "no_cleanup_flag", "bias_field_smoothing_val", "image_type", "bet_f_param"], "name": "Optional Parameters"}], "outputfiles": [{"description": "A folder containing the output files for fsl_anat. Includes outputs for the images, reorientation, cropping, bias correction, registration, brain extraction, and segmentation.", "list": false, "id": "folder_out", "optional": false, "path-template": "[OUTPUT_DIR].anat", "name": "Output folder"}], "suggestedresources": {"walltime-estimate": 16000}, "onlineplatformurls": ["https://portal.cbrain.mcgill.ca"], "ark_id": "https://n2t.net/ark:/70798/p7f5z1kh530bg2824g", "platforms": [{"img": "/static/img/run_on_cbrain_green.png", "uri": "/cbrainredirect?cbrainurl=https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id%3D62"}]}, {"id": "zenodo.4043546", "title": "FreeSurfer-Recon-all", "description": "Performs all, or any part of, the FreeSurfer cortical reconstruction process (https://surfer.nmr.mgh.harvard.edu/fswiki/recon-all).", "publicationdate": "2020-09-22", "deprecated": false, "downloads": 1157, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.1.1", "doi": "10.5281/zenodo.4043546", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "suggestedresources": {"ram": 10240, "walltime-estimate": 960, "cpu-cores": 1}, "outputfiles": [{"name": "Output", "optional": false, "description": "The subject data upon which to operate ", "id": "subjid_output", "path-template": "[SUBJID]"}], "name": "FreeSurfer-Recon-all", "containerimage": {"index": "docker://", "image": "freesurfer/freesurfer:7.1.1", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; recon-all [SUBJID] [INPUT] [DIRECTIVES] [QCACHE] [MPRAGE] [3T] [CW256] [NOTAL-CHECK] [HYPPOCAMPAL-SUBFIELDS] [BRAINSTEM-STRUCTURES] [NO-WSGCAATLAS] [NO-SKULLSTRIP]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "Output name", "command-line-flag": "-subjid", "optional": false, "value-key": "[SUBJID]", "type": "String", "id": "subjid"}, {"name": "NIFTI file", "id": "input", "optional": false, "value-key": "[INPUT]", "description": "Single NIFTI file from series.", "command-line-flag": "-i", "type": "File"}, {"name": "Directive", "default-value": "-all", "value-key": "[DIRECTIVES]", "optional": false, "type": "String", "id": "directives", "value-choices": ["-all", "-autorecon1", "-autorecon2", "-autorecon2-cp", "-autorecon2-wm", "-autorecon2-inflate1", "-autorecon2-perhemi", "-autorecon3"]}, {"name": "qcache", "id": "qcache_flag", "optional": true, "value-key": "[QCACHE]", "description": "Produce the pre-cached files required by the Qdec utility, allowing rapid analysis of group data.", "command-line-flag": "-qcache", "type": "Flag"}, {"name": "mprage", "id": "mprage_flag", "optional": true, "value-key": "[MPRAGE]", "description": "Assume scan parameters are MGH MP-RAGE protocol.", "command-line-flag": "-mprage", "type": "Flag"}, {"name": "3T", "id": "3T_flag", "optional": true, "value-key": "[3T]", "description": "The -3T flag enables two specific options in recon-all for images acquired with a 3T scanner:  3T-specific NU intensity correction parameters are used in the Non-Uniform normalization stage, and the Schwartz 3T atlas is used for Talairach alignment", "command-line-flag": "-3T", "type": "Flag"}, {"name": "cw256", "id": "cw256_flag", "optional": true, "value-key": "[CW256]", "description": "Include this flag after -autorecon1 if images have a FOV > 256.", "command-line-flag": "-cw256", "type": "Flag"}, {"name": "Notal check", "id": "notal_flag", "optional": true, "value-key": "[NOTAL-CHECK]", "description": "Skip the automatic failure detection of Talairach alignment.", "command-line-flag": "-notal-check", "type": "Flag"}, {"name": "Hippocampal-subfileds-T1", "id": "hippocampal_subfields_T1_flag", "optional": true, "value-key": "[HYPPOCAMPAL-SUBFIELDS]", "description": "Segmentation of hippocampal subfields using input T1 scan.", "command-line-flag": "-hippocampal-subfields-T1", "type": "Flag"}, {"name": "Brainstem Structures", "id": "brainstem_structures_flag", "optional": true, "value-key": "[BRAINSTEM-STRUCTURES]", "description": "Segmentation of brainstem structures.", "command-line-flag": "-brainstem-structures", "type": "Flag"}, {"name": "No wsgcaatlas", "id": "no_wsgcaatlas_flag", "optional": true, "value-key": "[NO-WSGCAATLAS]", "description": "Do not use GCA atlas when skull stripping.", "command-line-flag": "-no-wsgcaatlas", "type": "Flag"}, {"name": "No skull strip", "id": "noskullstrip_flag", "optional": true, "value-key": "[NO-SKULLSTRIP]", "description": "Exclude skull strip step.", "command-line-flag": "-noskullstrip", "type": "Flag"}], "custom": {"cbrain:author": "Natacha Beck <natacha.beck@mcgill.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7q4hjgc84b080wh6j", "platforms": [{"img": "/static/img/run_on_cbrain_green.png", "uri": "/cbrainredirect?cbrainurl=https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id%3D282"}]}, {"id": "zenodo.4010734", "title": "SPARK (stage 1 of 3)", "description": "SParsity-based Analysis of Reliable K-hubness (SPARK) for brain fMRI functional connectivity", "publicationdate": "2020-09-01", "deprecated": false, "downloads": 1127, "author": "Multi FunkIm", "version": "v1.2.2", "doi": "10.5281/zenodo.4010734", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["neuroinformatics", "fmri", "neuroimaging"]}, "name": "SPARK (stage 1 of 3)", "commandline": "spark --SETUP [FMRI] [OUT_DIR] [MASK] [NB_RESAMPLINGS] [NETWORK_SCALES] [NB_ITERATIONS] [P_VALUE] [RESAMPLING_METHOD] [BLOCK_WINDOW_LENGTH] [DICT_INIT_METHOD] [SPARSE_CODING_METHOD] [PRESERVE_DC_ATOM] [VERBOSE] && spark --RUN --stage A [FMRI] [OUT_DIR] [VERBOSE]", "containerimage": {"image": "multifunkim/spark-matlab:cbrain-mcv97", "index": "docker://", "type": "singularity"}, "groups": [{"id": "bootstrap_resampling", "members": ["nb_resamplings", "resampling_method", "block_window_length"], "name": "Bootstrap resampling"}, {"id": "sparse_dict_learning", "members": ["network_scales", "nb_iterations", "dict_init_method", "sparse_coding_method", "preserve_dc_atom"], "name": "Sparse dictionary learning"}, {"id": "k_hubness_map_generation", "members": ["p_value"], "name": "k-hubness map generation"}], "inputs": [{"command-line-flag": "--fmri", "description": "Path (absolute or relative) to the fMRI data to analyze. Notes: - This file should be a valid fMRI file of a BIDS dataset. - The filename will be used to name the outputs, for example: 'kmap_sub-01_task-rest_bold.mat'.", "id": "fmri", "name": "fMRI data", "optional": false, "type": "File", "value-key": "[FMRI]"}, {"command-line-flag": "--out-dir", "description": "Path (absolute or relative) to the output directory (old files might get replaced). By default, a new directory named after the specified input --fmri is created relative this output directory --out-dir to avoid conflicts. To change this default setting, use --move-outputs (useful to merge results of multiple analyses).", "id": "out_dir", "name": "Output directory name", "optional": false, "type": "String", "value-key": "[OUT_DIR]"}, {"command-line-flag": "--mask", "description": "Path (absolute or relative) to the grey-matter mask. (file formats: MINC, NIfTI)", "id": "mask", "name": "Grey-matter mask", "optional": false, "type": "File", "value-key": "[MASK]"}, {"command-line-flag": "--nb-resamplings", "description": "Number of bootstrap resamplings at the individual level. (recommended: 100)", "default-value": 100, "id": "nb_resamplings", "integer": true, "minimum": 2, "name": "Number of resamplings", "optional": false, "type": "Number", "value-key": "[NB_RESAMPLINGS]"}, {"command-line-flag": "--network-scales", "description": "Three integers, respectively: [begin] [step] [end], used to create a regularly-spaced vector. In order to specify a single number, for instance '12', enter the same number for [begin] and [end], as: '--network-scales 12 1 12'. The numbers in the vector correspond to the range of network scales to be tested. An optimal network scale will be automatically estimated from the vector. (recommended: 10 2 30)", "default-value": [10, 2, 30], "id": "network_scales", "integer": true, "list": true, "max-list-entries": 3, "min-list-entries": 3, "minimum": 1, "name": "Network scales", "optional": false, "type": "Number", "value-key": "[NETWORK_SCALES]"}, {"command-line-flag": "--nb-iterations", "description": "Number of iterations for the sparse dictionary learning.  (recommended: 20)", "default-value": 20, "id": "nb_iterations", "integer": true, "minimum": 2, "name": "Number of iterations", "optional": false, "type": "Number", "value-key": "[NB_ITERATIONS]"}, {"command-line-flag": "--p-value", "default-value": 0.05, "description": "Significance level, using a Z-test, for removing inconsistent elements in the average sparse coefficients (considered as Gaussian noise) after spatial clustering.", "id": "p_value", "maximum": 1, "minimum": 0, "name": "P-Value", "optional": false, "type": "Number", "value-key": "[P_VALUE]"}, {"command-line-flag": "--resampling-method", "default-value": "CBB", "description": "Method (from NIAK) used to resample the data under the null hypothesis. Note: If 'CBB' is selected, the option --block-window-length is used. - CBB: Circular-block-bootstrap sample of multiple time series. - AR1B: Bootstrap sample of multiple time series based on a semiparametric scheme mixing an auto-regressive temporal model and i.i.d. bootstrap of the 'innovations'. - AR1G: Bootstrap sample of multiple time series based on a parametric model of Gaussian data with arbitrary spatial correlations and first-order auto-regressive temporal correlations.", "id": "resampling_method", "name": "Resampling method", "optional": true, "type": "String", "value-choices": ["CBB", "AR1B", "AR1G"], "value-disables": {"AR1B": ["block_window_length"], "AR1G": ["block_window_length"], "CBB": []}, "value-key": "[RESAMPLING_METHOD]", "value-requires": {"AR1B": [], "AR1G": [], "CBB": ["block_window_length"]}}, {"command-line-flag": "--block-window-length", "default-value": [10, 1, 30], "description": "Three numbers, respectively: [begin] [step] [end], used to create a regularly-spaced vector. In order to specify a single number, for instance '12', enter the same number for [begin] and [end], as: '--block-window-length 12 1 12'. A number in the vector corresponds to a window length used in the circular block bootstrap. The unit of the window length is \u2018time-point\u2019 with each time-point indicating a 3D scan at each TR. If the vector contains multiple numbers, then a number will be randomly selected from it at each resampling. It is recommended to use window lengths greater or equal to sqrt(T), where T is the total number of time points in the fMRI time-course. It is also recommended to randomize the window length used at each resampling to reduce a bias by window size.", "id": "block_window_length", "integer": true, "list": true, "max-list-entries": 3, "min-list-entries": 3, "minimum": 1, "name": "Block window length", "optional": true, "type": "Number", "value-key": "[BLOCK_WINDOW_LENGTH]"}, {"command-line-flag": "--dict-init-method", "default-value": "GivenMatrix", "description": "If 'GivenMatrix' is selected, then the dictionary will be initialized by a random permutation of the raw data obtained in step 1. If 'DataElements' is selected, then the dictionary will be initialized by the first N (number of atoms) columns in the raw data obtained in step 1.", "id": "dict_init_method", "name": "Dictionary initialization method", "optional": true, "type": "String", "value-choices": ["GivenMatrix", "DataElements"], "value-key": "[DICT_INIT_METHOD]"}, {"command-line-flag": "--sparse-coding-method", "default-value": "Thresholding", "description": "Sparse coding method for the sparse dictionary learning.", "id": "sparse_coding_method", "name": "Sparse coding method", "optional": true, "type": "String", "value-choices": ["OMP", "Thresholding"], "value-key": "[SPARSE_CODING_METHOD]"}, {"command-line-flag": "--preserve-dc-atom", "description": "If set, then the first atom will be set to a constant and will never change, while all the other atoms will be trained and updated.", "id": "preserve_dc_atom", "name": "Perserve DC atom", "optional": true, "type": "Flag", "value-key": "[PRESERVE_DC_ATOM]"}, {"command-line-flag": "--verbose", "description": "If set, the program will provide some additional details.", "id": "verbose", "name": "Verbose", "optional": true, "type": "Flag", "value-key": "[VERBOSE]"}], "outputfiles": [{"description": "Results directory containing:  k-hubness maps, atom maps and intermediate files. (file formats: MINC, NIfTI)", "id": "result", "name": "Results directory", "optional": false, "path-template": "[OUT_DIR]"}], "suggestedresources": {"cpu-cores": 1, "ram": 8, "walltime-estimate": 100000}, "custom": {"cbrain:inherits-from-class": "CbrainTask::SparkHandler"}, "toolversion": "v1.2.2", "ark_id": "https://n2t.net/ark:/70798/p7xm2tjsx88h94wn2r", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.4010740", "title": "SPARK (stage 3 of 3)", "description": "SParsity-based Analysis of Reliable K-hubness (SPARK) for brain fMRI functional connectivity", "publicationdate": "2020-09-01", "deprecated": false, "downloads": 1119, "author": "Multi FunkIm", "version": "v1.2.2", "doi": "10.5281/zenodo.4010740", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["neuroinformatics", "fmri", "neuroimaging"]}, "name": "SPARK (stage 3 of 3)", "commandline": "spark --RUN --stage C [FMRI] [OUT_DIR] [VERBOSE] && spark --WRAP-UP --move-outputs [FMRI] [OUT_DIR] [VERBOSE]", "containerimage": {"image": "multifunkim/spark-matlab:cbrain-mcv97", "index": "docker://", "type": "singularity"}, "inputs": [{"command-line-flag": "--fmri", "description": "Path (absolute or relative) to the fMRI data to analyze. Notes: - This file should be a valid fMRI file of a BIDS dataset. - The filename will be used to name the outputs, for example: 'kmap_sub-01_task-rest_bold.mat'.", "id": "fmri", "name": "fMRI data", "optional": false, "type": "File", "value-key": "[FMRI]"}, {"command-line-flag": "--out-dir", "description": "Path (absolute or relative) to the output directory (old files might get replaced). By default, a new directory named after the specified input --fmri is created relative this output directory --out-dir to avoid conflicts. To change this default setting, use --move-outputs (useful to merge results of multiple analyses).", "id": "out_dir", "name": "Output directory name", "optional": false, "type": "String", "value-key": "[OUT_DIR]"}, {"command-line-flag": "--verbose", "description": "If set, the program will provide some additional details.", "id": "verbose", "name": "Verbose", "optional": true, "type": "Flag", "value-key": "[VERBOSE]"}], "outputfiles": [{"description": "Results directory containing:  k-hubness maps, atom maps and intermediate files. (file formats: MINC, NIfTI)", "id": "result", "name": "Results directory", "optional": false, "path-template": "[OUT_DIR]"}], "suggestedresources": {"cpu-cores": 1, "ram": 8, "walltime-estimate": 100000}, "custom": {"cbrain:inherits-from-class": "CbrainTask::SparkHandler"}, "toolversion": "v1.2.2", "ark_id": "https://n2t.net/ark:/70798/p72vx84c1954t6gcv9", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.4010743", "title": "BEst - wMEM", "description": "EEG/MEG source localisation with wavelet-based Maximum Entropy on the Mean - wMEM (time-scale representation)", "publicationdate": "2020-09-01", "deprecated": false, "downloads": 1115, "author": "Multi FunkIm", "version": "1.2", "doi": "10.5281/zenodo.4010743", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": "neuroinformatics"}, "commandline": "best [INPUT_DATA] [OUTPUT_DIR_NAME] [MEM_METHOD] [SENSORS_TYPES] [RECONSTRUCTION_WINDOW] [BASELINE_WINDOW] [BASELINE] [NORMALIZATION] [CLUSTERING_METHOD] [MSP_THRESHOLD_METHOD] [MSP_THRESHOLD] [NEIGHBORHOOD_ORDER] [SPATIAL_SMOOTHING] [ACTIVE_MEAN_INIT] [ACTIVE_PROBA_INIT] [LAMBDA_INIT] [ACTIVE_PROBA_THRESHOLD] [ACTIVE_VAR_COEF] [INACTIVE_VAR_COEF] [NOISE_COV_METHOD] [OPTIM_METHOD] [FREQUENCIES] [WAVELET_TYPE] [VANISHING_MOMENTS] [COEF_SHRINKAGE] [USE_PARALLEL] [MAX_WORKERS]", "containerimage": {"image": "multifunkim/best:cbrain-mcv97", "index": "docker://", "type": "singularity"}, "groups": [{"id": "data_definition", "members": ["sensors_types", "reconstruction_window", "baseline", "baseline_window", "normalization"], "name": "Data definition"}, {"id": "job_spec", "members": ["use_parallel", "max_workers"], "name": "Job specifications"}, {"id": "oscillations_options", "members": ["frequencies"], "name": "Oscillations options"}, {"id": "clustering", "members": ["clustering_method", "msp_threshold_method", "msp_threshold", "neighborhood_order", "spatial_smoothing"], "name": "Clustering"}, {"id": "model_priors", "members": ["active_mean_init", "active_proba_init", "lambda_init", "active_proba_threshold", "active_var_coef", "inactive_var_coef"], "name": "Model priors"}, {"id": "solver_options", "members": ["noise_cov_method", "optim_method"], "name": "Solver options"}, {"id": "wavelet_processing", "members": ["wavelet_type", "vanishing_moments", "coef_shrinkage"], "name": "Wavelet processing"}], "inputs": [{"command-line-flag": "inputData", "description": "The input data: a directory or a file (.mat, .tgz, .tar.gz, .tar) as exported from Brainstorm.", "id": "input_data", "name": "Input data", "optional": false, "type": "File", "value-key": "[INPUT_DATA]"}, {"command-line-flag": "outputDirName", "default-value": "cbrain-wmem-sources", "description": "Name of the output directory", "id": "output_dir_name", "name": "Output directory name", "optional": false, "type": "String", "value-key": "[OUTPUT_DIR_NAME]"}, {"command-line-flag": "memMethod", "default-value": "wMEM", "id": "mem_method", "name": "MEM method", "optional": false, "type": "String", "value-choices": ["wMEM"], "value-key": "[MEM_METHOD]"}, {"command-line-flag": "sensorsTypes", "description": "The data sensors types to process.", "id": "sensors_types", "name": "Sensors types", "optional": false, "type": "String", "value-choices": ["EEG", "MEG"], "value-key": "[SENSORS_TYPES]"}, {"command-line-flag": "reconstructionWindow", "description": "This is the portion of your input recording data to reconstruct. The time window should be specified by two (increasing) numbers in seconds separated by a blank space: 'TIME_BEGIN TIME_END'. For example: '-0.5 1' means from -0.5 to 1 s.", "id": "reconstruction_window", "name": "Reconstruction time window", "optional": false, "type": "String", "value-key": "[RECONSTRUCTION_WINDOW]"}, {"command-line-flag": "baselineWindow", "description": "This is the portion of your baseline data to use for estimating a noise covariance matrix. The time window should be specified by two (increasing) numbers in seconds separated by a blank space: 'TIME_BEGIN TIME_END'. For example: '-1 0.5' means from -1 to 0.5 s.", "id": "baseline_window", "name": "Baseline time window", "optional": false, "type": "String", "value-key": "[BASELINE_WINDOW]"}, {"command-line-flag": "baseline", "description": "This is your baseline file (.mat, .tgz, .tar.gz, .tar) as exported from Brainstorm. If no baseline file is specified, then the baseline data will be extracted from within the (input) recording data.", "id": "baseline", "name": "Baseline data", "optional": true, "type": "File", "value-key": "[BASELINE]"}, {"command-line-flag": "normalization", "default-value": "fixed", "description": "Normalization strategy used for computing the solution. If set to 'adaptive', then a minimum norm solution will be used to normalize the data.", "id": "normalization", "name": "Normalization", "optional": true, "type": "String", "value-choices": ["adaptive", "fixed"], "value-key": "[NORMALIZATION]"}, {"command-line-flag": "useParallel", "default-value": "true", "description": "If set, then the samples will be reconstructed in parallel.", "id": "use_parallel", "name": "Parallel computing", "optional": true, "type": "String", "value-choices": ["true", "false"], "value-disables": {"true": [], "false": ["max_workers"]}, "value-key": "[USE_PARALLEL]", "value-requires": {"true": ["max_workers"], "false": []}}, {"command-line-flag": "maxWorkers", "default-value": 12, "description": "Maximum number of workers for parallel processing.", "id": "max_workers", "integer": true, "minimum": 2, "name": "Number of workers", "optional": true, "type": "Number", "value-key": "[MAX_WORKERS]"}, {"command-line-flag": "frequencies", "default-value": "all", "description": "Frequencies used to determine the scales to analyze. Frequencies can be specified as follows: 'all' for selecting all scales; '11.5' for selecting the scale containing the frequency 11.5 Hz; '8-13' for selecting the scales containing the frequencies from 8 to 13 Hz; '1-3;8-13' for selecting the scales containing the frequencies from both 1 to 3 Hz and 8 to 13 Hz. The character '.' indicates the decimal point, '-' indicate a range, and ';' is used as a separator.", "id": "frequencies", "name": "Frequencies analyzed", "optional": true, "type": "String", "value-key": "[FREQUENCIES]"}, {"command-line-flag": "clusteringMethod", "default-value": "wavelet-adaptive", "description": "With the method 'wavelet-adaptive', the size of time windows used for clustering is adapted to the size of the time-frequency or time-scale boxes.", "id": "clustering_method", "name": "Clustering method", "optional": true, "type": "String", "value-choices": ["wavelet-adaptive"], "value-key": "[CLUSTERING_METHOD]"}, {"command-line-flag": "mspThresholdMethod", "default-value": "fdr", "description": "Thresholding method applied to the MSP scores. If set to 'fdr', then thresholds will be learned from baseline. Otherwise, the option 'MSP scores threshold' is used.", "id": "msp_threshold_method", "name": "MSP scores threshold method", "optional": true, "type": "String", "value-choices": ["arbitrary", "fdr"], "value-disables": {"arbitrary": [], "fdr": ["msp_threshold"]}, "value-key": "[MSP_THRESHOLD_METHOD]", "value-requires": {"arbitrary": ["msp_threshold"], "fdr": []}}, {"command-line-flag": "mspThreshold", "default-value": 0, "description": "This is used when 'MSP scores threshold method' is set to 'arbitrary'. A whole brain parcellation is done if this threshold is set to 0.", "id": "msp_threshold", "maximum": 1, "minimum": 0, "name": "MSP scores threshold", "optional": true, "type": "Number", "value-key": "[MSP_THRESHOLD]"}, {"command-line-flag": "neighborhoodOrder", "default-value": 4, "description": "This is used to set the maximal size of cortical parcels (initial source configuration for MEM).", "id": "neighborhood_order", "integer": true, "minimum": 0, "name": "Neighborhood order", "optional": true, "type": "Number", "value-key": "[NEIGHBORHOOD_ORDER]"}, {"command-line-flag": "spatialSmoothing", "default-value": 0.6, "description": "Smoothness of MEM solution: spatial regularization of the MEM (linear decay of spatial source correlations).", "id": "spatial_smoothing", "maximum": 1, "minimum": 0, "name": "Spatial smoothing", "optional": true, "type": "Number", "value-key": "[SPATIAL_SMOOTHING]"}, {"command-line-flag": "activeMeanInit", "default-value": "2: null hypothesis", "description": "Initialization method of the active mean of each cluster.", "id": "active_mean_init", "name": "Active mean initialization", "optional": true, "type": "String", "value-choices": ["1: regular minimum norm", "2: null hypothesis", "3: MSP-regularized minimum norm", "4: L-curve optimized Minimum Norm Estimate"], "value-key": "[ACTIVE_MEAN_INIT]"}, {"command-line-flag": "activeProbaInit", "default-value": "3: median MSP scores", "description": "Initialization method of the active probability of each cluster.", "id": "active_proba_init", "name": "Active probability initialization", "optional": true, "type": "String", "value-choices": ["1: mean MSP scores", "2: max MSP scores", "3: median MSP scores", "4: equal to 0.5", "5: equal to 1"], "value-key": "[ACTIVE_PROBA_INIT]"}, {"command-line-flag": "lambdaInit", "default-value": "1: random", "description": "Initialization method of the sensor weights vector.", "id": "lambda_init", "name": "Lambda initialization", "optional": true, "type": "String", "value-choices": ["0: null hypothesis (vector of zeros)", "1: random"], "value-key": "[LAMBDA_INIT]"}, {"command-line-flag": "activeProbaThreshold", "default-value": 0.1, "description": "A threshold used to exclude clusters with low probability from the computed solution.", "id": "active_proba_threshold", "maximum": 1, "minimum": 0, "name": "Active probability threshold", "optional": true, "type": "Number", "value-key": "[ACTIVE_PROBA_THRESHOLD]"}, {"command-line-flag": "activeVarCoef", "default-value": 0.05, "description": "A weight applied to the active variance of each cluster.", "id": "active_var_coef", "maximum": 1, "minimum": 0, "name": "Active variance coefficient", "optional": true, "type": "Number", "value-key": "[ACTIVE_VAR_COEF]"}, {"command-line-flag": "inactiveVarCoef", "default-value": 0, "description": "A weight applied to the inactive variance of each cluster.", "id": "inactive_var_coef", "maximum": 1, "minimum": 0, "name": "Inactive variance coefficient", "optional": true, "type": "Number", "value-key": "[INACTIVE_VAR_COEF]"}, {"command-line-flag": "noiseCovMethod", "default-value": "5: Scalar matrix", "description": "The performance of the MEM is tied to a consistent estimation of the noise covariance matrix. We recommend using the method: '5: Scalar matrix'.", "id": "noise_cov_method", "name": "Noise covariance method", "optional": true, "type": "String", "value-choices": ["4: Diagonal matrix", "5: Scalar matrix"], "value-key": "[NOISE_COV_METHOD]"}, {"command-line-flag": "optimMethod", "default-value": "fminunc", "description": "'fminunc': MATLAB standard unconstrained optimization routine. 'minfunc': (faster) Unconstrained optimization routine, copyright Mark Schmidt, INRIA.", "id": "optim_method", "name": "Optimization routine", "optional": true, "type": "String", "value-choices": ["fminunc", "minfunc"], "value-key": "[OPTIM_METHOD]"}, {"command-line-flag": "waveletType", "default-value": "rdw", "description": "'rdw': Discrete wavelet transform (real Daubechies).", "id": "wavelet_type", "name": "Wavelet type", "optional": true, "type": "String", "value-choices": ["rdw"], "value-key": "[WAVELET_TYPE]"}, {"command-line-flag": "vanishingMoments", "default-value": 4, "description": "High polynomial order filtered out by the wavelet (compromise between frequency resolution and temporal decorrelation).", "id": "vanishing_moments", "integer": true, "minimum": 0, "maximum": 4, "name": "Vanishing moments", "optional": true, "type": "Number", "value-key": "[VANISHING_MOMENTS]"}, {"command-line-flag": "coefShrinkage", "default-value": 1, "description": "For discrete wavelet transform denoising: 0 means no denoising, and 1 means soft denoising (removing low energy coefficients).", "id": "coef_shrinkage", "minimum": 0, "maximum": 1, "name": "Coefficient shrinkage", "optional": true, "type": "Number", "value-key": "[COEF_SHRINKAGE]"}], "name": "BEst - wMEM", "outputfiles": [{"description": "Output data ready to be imported in Brainstorm.", "id": "output_data", "name": "Output data", "optional": false, "path-template": "[OUTPUT_DIR_NAME]"}], "suggestedresources": {"cpu-cores": 12, "ram": 60, "walltime-estimate": 100000}, "toolversion": "1.2", "ark_id": "https://n2t.net/ark:/70798/p796cs4f65z5c6j6r8", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.4010742", "title": "BEst - cMEM", "description": "EEG/MEG source localisation with Maximum Entropy on the Mean - cMEM (time series representation)", "publicationdate": "2020-09-01", "deprecated": false, "downloads": 1114, "author": "Multi FunkIm", "version": "1.2", "doi": "10.5281/zenodo.4010742", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": "neuroinformatics"}, "commandline": "best [INPUT_DATA] [OUTPUT_DIR_NAME] [MEM_METHOD] [SENSORS_TYPES] [RECONSTRUCTION_WINDOW] [BASELINE_WINDOW] [BASELINE] [NORMALIZATION] [CLUSTERING_METHOD] [MSP_WINDOW] [MSP_THRESHOLD_METHOD] [MSP_THRESHOLD] [NEIGHBORHOOD_ORDER] [SPATIAL_SMOOTHING] [ACTIVE_MEAN_INIT] [ACTIVE_PROBA_INIT] [LAMBDA_INIT] [ACTIVE_PROBA_THRESHOLD] [ACTIVE_VAR_COEF] [INACTIVE_VAR_COEF] [NOISE_COV_METHOD] [OPTIM_METHOD] [USE_PARALLEL] [MAX_WORKERS]", "containerimage": {"image": "multifunkim/best:cbrain-mcv97", "index": "docker://", "type": "singularity"}, "groups": [{"id": "data_definition", "members": ["sensors_types", "reconstruction_window", "baseline", "baseline_window", "normalization"], "name": "Data definition"}, {"id": "job_spec", "members": ["use_parallel", "max_workers"], "name": "Job specifications"}, {"id": "clustering", "members": ["clustering_method", "msp_window", "msp_threshold_method", "msp_threshold", "neighborhood_order", "spatial_smoothing"], "name": "Clustering"}, {"id": "model_priors", "members": ["active_mean_init", "active_proba_init", "lambda_init", "active_proba_threshold", "active_var_coef", "inactive_var_coef"], "name": "Model priors"}, {"id": "solver_options", "members": ["noise_cov_method", "optim_method"], "name": "Solver options"}], "inputs": [{"command-line-flag": "inputData", "description": "The input data: a directory or a file (.mat, .tgz, .tar.gz, .tar) as exported from Brainstorm.", "id": "input_data", "name": "Input data", "optional": false, "type": "File", "value-key": "[INPUT_DATA]"}, {"command-line-flag": "outputDirName", "default-value": "cbrain-cmem-sources", "description": "Name of the output directory", "id": "output_dir_name", "name": "Output directory name", "optional": false, "type": "String", "value-key": "[OUTPUT_DIR_NAME]"}, {"command-line-flag": "memMethod", "default-value": "cMEM", "id": "mem_method", "name": "MEM method", "optional": false, "type": "String", "value-choices": ["cMEM"], "value-key": "[MEM_METHOD]"}, {"command-line-flag": "sensorsTypes", "description": "The data sensors types to process.", "id": "sensors_types", "name": "Sensors types", "optional": false, "type": "String", "value-choices": ["EEG", "MEG", "EEG+MEG"], "value-key": "[SENSORS_TYPES]"}, {"command-line-flag": "reconstructionWindow", "description": "This is the portion of your input recording data to reconstruct. The time window should be specified by two (increasing) numbers in seconds separated by a blank space: 'TIME_BEGIN TIME_END'. For example: '-0.5 1' means from -0.5 to 1 s.", "id": "reconstruction_window", "name": "Reconstruction time window", "optional": false, "type": "String", "value-key": "[RECONSTRUCTION_WINDOW]"}, {"command-line-flag": "baselineWindow", "description": "This is the portion of your baseline data to use for estimating a noise covariance matrix. The time window should be specified by two (increasing) numbers in seconds separated by a blank space: 'TIME_BEGIN TIME_END'. For example: '-1 0.5' means from -1 to 0.5 s.", "id": "baseline_window", "name": "Baseline time window", "optional": false, "type": "String", "value-key": "[BASELINE_WINDOW]"}, {"command-line-flag": "baseline", "description": "This is your baseline file (.mat, .tgz, .tar.gz, .tar) as exported from Brainstorm. If no baseline file is specified, then the baseline data will be extracted from within the (input) recording data.", "id": "baseline", "name": "Baseline data", "optional": true, "type": "File", "value-key": "[BASELINE]"}, {"command-line-flag": "normalization", "default-value": "adaptive", "description": "Normalization strategy used for computing the solution. If set to 'adaptive', then a minimum norm solution will be used to normalize the data.", "id": "normalization", "name": "Normalization", "optional": true, "type": "String", "value-choices": ["adaptive", "fixed"], "value-key": "[NORMALIZATION]"}, {"command-line-flag": "useParallel", "default-value": "true", "description": "If set, then the samples will be reconstructed in parallel.", "id": "use_parallel", "name": "Parallel computing", "optional": true, "type": "String", "value-choices": ["true", "false"], "value-disables": {"true": [], "false": ["max_workers"]}, "value-key": "[USE_PARALLEL]", "value-requires": {"true": ["max_workers"], "false": []}}, {"command-line-flag": "maxWorkers", "default-value": 12, "description": "Maximum number of workers for parallel processing.", "id": "max_workers", "integer": true, "minimum": 2, "name": "Number of workers", "optional": true, "type": "Number", "value-key": "[MAX_WORKERS]"}, {"command-line-flag": "clusteringMethod", "default-value": "static", "description": "With the method 'blockwise', cortical parcels are computed within consecutive time windows specified with the option: 'MSP window'. With the method 'static', only one set of cortical parcels is computed for the whole data.", "id": "clustering_method", "name": "Clustering method", "optional": true, "type": "String", "value-choices": ["static", "blockwise"], "value-disables": {"blockwise": [], "static": ["msp_window"]}, "value-key": "[CLUSTERING_METHOD]", "value-requires": {"blockwise": ["msp_window"], "static": []}}, {"command-line-flag": "mspWindow", "default-value": 10, "description": "Used when clustering method is set to 'blockwise', this is the size of the sliding window in millisecond (ms).", "id": "msp_window", "minimum": 0, "name": "MSP window", "optional": true, "type": "Number", "value-key": "[MSP_WINDOW]"}, {"command-line-flag": "mspThresholdMethod", "default-value": "arbitrary", "description": "Thresholding method applied to the MSP scores. If set to 'fdr', then thresholds will be learned from baseline. Otherwise, the option 'MSP scores threshold' is used.", "id": "msp_threshold_method", "name": "MSP scores threshold method", "optional": true, "type": "String", "value-choices": ["arbitrary", "fdr"], "value-disables": {"arbitrary": [], "fdr": ["msp_threshold"]}, "value-key": "[MSP_THRESHOLD_METHOD]", "value-requires": {"arbitrary": ["msp_threshold"], "fdr": []}}, {"command-line-flag": "mspThreshold", "default-value": 0, "description": "This is used when 'MSP scores threshold method' is set to 'arbitrary'. A whole brain parcellation is done if this threshold is set to 0.", "id": "msp_threshold", "maximum": 1, "minimum": 0, "name": "MSP scores threshold", "optional": true, "type": "Number", "value-key": "[MSP_THRESHOLD]"}, {"command-line-flag": "neighborhoodOrder", "default-value": 4, "description": "This is used to set the maximal size of cortical parcels (initial source configuration for MEM).", "id": "neighborhood_order", "integer": true, "minimum": 0, "name": "Neighborhood order", "optional": true, "type": "Number", "value-key": "[NEIGHBORHOOD_ORDER]"}, {"command-line-flag": "spatialSmoothing", "default-value": 0.6, "description": "Smoothness of MEM solution: spatial regularization of the MEM (linear decay of spatial source correlations).", "id": "spatial_smoothing", "maximum": 1, "minimum": 0, "name": "Spatial smoothing", "optional": true, "type": "Number", "value-key": "[SPATIAL_SMOOTHING]"}, {"command-line-flag": "activeMeanInit", "default-value": "2: null hypothesis", "description": "Initialization method of the active mean of each cluster.", "id": "active_mean_init", "name": "Active mean initialization", "optional": true, "type": "String", "value-choices": ["1: regular minimum norm", "2: null hypothesis", "3: MSP-regularized minimum norm", "4: L-curve optimized Minimum Norm Estimate"], "value-key": "[ACTIVE_MEAN_INIT]"}, {"command-line-flag": "activeProbaInit", "default-value": "3: median MSP scores", "description": "Initialization method of the active probability of each cluster.", "id": "active_proba_init", "name": "Active probability initialization", "optional": true, "type": "String", "value-choices": ["1: mean MSP scores", "2: max MSP scores", "3: median MSP scores", "4: equal to 0.5", "5: equal to 1"], "value-key": "[ACTIVE_PROBA_INIT]"}, {"command-line-flag": "lambdaInit", "default-value": "1: random", "description": "Initialization method of the sensor weights vector.", "id": "lambda_init", "name": "Lambda initialization", "optional": true, "type": "String", "value-choices": ["0: null hypothesis (vector of zeros)", "1: random"], "value-key": "[LAMBDA_INIT]"}, {"command-line-flag": "activeProbaThreshold", "default-value": 0, "description": "A threshold used to exclude clusters with low probability from the computed solution.", "id": "active_proba_threshold", "maximum": 1, "minimum": 0, "name": "Active probability threshold", "optional": true, "type": "Number", "value-key": "[ACTIVE_PROBA_THRESHOLD]"}, {"command-line-flag": "activeVarCoef", "default-value": 0.05, "description": "A weight applied to the active variance of each cluster.", "id": "active_var_coef", "maximum": 1, "minimum": 0, "name": "Active variance coefficient", "optional": true, "type": "Number", "value-key": "[ACTIVE_VAR_COEF]"}, {"command-line-flag": "inactiveVarCoef", "default-value": 0, "description": "A weight applied to the inactive variance of each cluster.", "id": "inactive_var_coef", "maximum": 1, "minimum": 0, "name": "Inactive variance coefficient", "optional": true, "type": "Number", "value-key": "[INACTIVE_VAR_COEF]"}, {"command-line-flag": "noiseCovMethod", "default-value": "2: Diagonal matrix", "description": "The performance of the MEM is tied to a consistent estimation of the noise covariance matrix. We recommend using the method: '2: Diagonal matrix'.", "id": "noise_cov_method", "name": "Noise covariance method", "optional": true, "type": "String", "value-choices": ["0: Identity matrix", "1: Scalar matrix", "2: Diagonal matrix", "3: Full", "4: Wavelet-based"], "value-key": "[NOISE_COV_METHOD]"}, {"command-line-flag": "optimMethod", "default-value": "fminunc", "description": "'fminunc': MATLAB standard unconstrained optimization routine. 'minfunc': (faster) Unconstrained optimization routine, copyright Mark Schmidt, INRIA.", "id": "optim_method", "name": "Optimization routine", "optional": true, "type": "String", "value-choices": ["fminunc", "minfunc"], "value-key": "[OPTIM_METHOD]"}], "name": "BEst - cMEM", "outputfiles": [{"description": "Output data ready to be imported in Brainstorm.", "id": "output_data", "name": "Output data", "optional": false, "path-template": "[OUTPUT_DIR_NAME]"}], "suggestedresources": {"cpu-cores": 12, "ram": 60, "walltime-estimate": 100000}, "toolversion": "1.2", "ark_id": "https://n2t.net/ark:/70798/p7chpmgdx0kvp44zsq", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.4010735", "title": "SPARK (stage 2 of 3)", "description": "SParsity-based Analysis of Reliable K-hubness (SPARK) for brain fMRI functional connectivity", "publicationdate": "2020-09-01", "deprecated": false, "downloads": 1109, "author": "Multi FunkIm", "version": "v1.2.2", "doi": "10.5281/zenodo.4010735", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["neuroinformatics", "fmri", "neuroimaging"]}, "name": "SPARK (stage 2 of 3)", "commandline": "spark --RUN --stage B [FMRI] [OUT_DIR] [VERBOSE] [JOBS-INDICES]", "containerimage": {"image": "multifunkim/spark-matlab:cbrain-mcv97", "index": "docker://", "type": "singularity"}, "inputs": [{"command-line-flag": "--fmri", "description": "Path (absolute or relative) to the fMRI data to analyze. Notes: - This file should be a valid fMRI file of a BIDS dataset. - The filename will be used to name the outputs, for example: 'kmap_sub-01_task-rest_bold.mat'.", "id": "fmri", "name": "fMRI data", "optional": false, "type": "File", "value-key": "[FMRI]"}, {"command-line-flag": "--out-dir", "description": "Path (absolute or relative) to the output directory (old files might get replaced). By default, a new directory named after the specified input --fmri is created relative this output directory --out-dir to avoid conflicts. To change this default setting, use --move-outputs (useful to merge results of multiple analyses).", "id": "out_dir", "name": "Output directory name", "optional": false, "type": "String", "value-key": "[OUT_DIR]"}, {"command-line-flag": "--verbose", "description": "If set, the program will provide some additional details.", "id": "verbose", "name": "Verbose", "optional": true, "type": "Flag", "value-key": "[VERBOSE]"}, {"command-line-flag": "--jobs-indices", "description": "Jobs indices to run. Must be lower or equal to nb_resamplings used during setup.", "id": "jobs_indices", "name": "Jobs indices", "optional": false, "type": "Number", "integer": true, "list": true, "min-list-entries": 1, "minimum": 1, "value-key": "[JOBS-INDICES]"}], "outputfiles": [{"description": "Results directory containing:  k-hubness maps, atom maps and intermediate files. (file formats: MINC, NIfTI)", "id": "result", "name": "Results directory", "optional": false, "path-template": "[OUT_DIR]"}], "suggestedresources": {"cpu-cores": 1, "ram": 8, "walltime-estimate": 100000}, "custom": {"cbrain:inherits-from-class": "CbrainTask::SparkHandler"}, "toolversion": "v1.2.2", "ark_id": "https://n2t.net/ark:/70798/p71jpnjqj6dgq0bqmf", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.4429271", "title": "shape_group_run", "description": "This tool takes FreeSurfer aseg.mgz files and generates homologous mesh representations of subcortical ROI boundaries and vertex-wise shape features for statistical analysis. Please cite the following work when using this tool: 1. Gutman, B.A., Madsen, S.K., Toga, A.W., Thompson, P.M.: A Family of Fast Spherical Registration Algorithms for Cortical Shapes. In: Multimodal Brain Image Analysis, vol. 8159, pp. 246-257. Springer International Publishing (2013) 2. Gutman, B.A., Wang, Y., Rajagopalan, P., Toga, A.W., Thompson, P.M.: Shape matching with medial curves and 1-D group-wise registration. In: Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on, pp. 716-719. (2012)", "publicationdate": "2021-01-08", "deprecated": false, "downloads": 765, "author": "ENIGMA", "version": "unknown", "doi": "10.5281/zenodo.4429271", "schemaversion": "0.5", "container": "docker", "tags": {"genetics": true, "ENIGMA": true}, "name": "shape_group_run", "toolversion": "unknown", "descriptorurl": "https://raw.githubusercontent.com/glatard/enigma_shape-docker/master/shape_group_run.json", "commandline": "chmod 700 [FREESURFER_SUBJECT_DIR]/mri && echo $(basename [FREESURFER_SUBJECT_DIR]) > ids.csv && shape_group_run.sh ids.csv $(dirname [FREESURFER_SUBJECT_DIR]) shape-results", "containerimage": {"image": "glatard/enigma_shape:latest", "type": "docker"}, "onlineplatformurls": ["https://portal.cbrain.mcgill.ca"], "inputs": [{"id": "freesurfer_subject_dir", "name": "Freesurfer subject output directory", "description": "A Freesurfer subject output directory, usually named after a subject id (e.g., '12345').", "type": "File", "value-key": "[FREESURFER_SUBJECT_DIR]"}], "outputfiles": [{"id": "outputs", "name": "Output directory", "path-template": "shape-results"}], "suggestedresources": {"walltime-estimate": 3600}, "ark_id": "https://n2t.net/ark:/70798/p7hk85zkp76g464vcg", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.4457865", "title": "BIDS App - ndmg", "description": "ndmg connectome estimation pipeline", "publicationdate": "2021-01-22", "deprecated": false, "downloads": 730, "author": "Greg Kiar", "version": "v0.1.0", "doi": "10.5281/zenodo.4457865", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "diffusion", "mri", "bids"]}, "commandline": "ndmg_bids BIDS_DIR OUTPUT_DIR ANALYSIS_LEVEL PARTICIPANT_LABEL SESSION_LABEL BUCKET REMOTE_PATH PUSH_DATA DATASET ATLAS MINIMAL HEMISPHERES LOG DEBUG", "containerimage": {"image": "bids/ndmg:v0.1.0", "index": "index.docker.io", "type": "docker"}, "inputs": [{"description": "The directory with the input dataset formatted according to the BIDS standard.", "id": "bids_dir", "name": "bids_dir", "optional": false, "type": "File", "value-key": "BIDS_DIR"}, {"description": "The directory where the output files should be stored. If you are running group level analysis this folder should be prepopulated with the results of the participant level analysis.", "id": "output_dir", "name": "output_dir", "optional": false, "type": "File", "value-key": "OUTPUT_DIR"}, {"description": "Level of the analysis that will be performed. Multiple participant level analyses can be run independently (in parallel) using the same output_dir.", "id": "analysis_level", "name": "analysis_level", "optional": false, "type": "String", "value-choices": ["participant", "group"], "value-key": "ANALYSIS_LEVEL"}, {"command-line-flag": "--participant_label", "description": "The label(s) of the participant(s) that should be analyzed. The label corresponds to sub-<participant_label> from the BIDS spec (so it does not include \"sub-\"). If this parameter is not provided all subjects should be analyzed. Multiple participants can be specified with a space separated list.", "id": "participant_label", "name": "participant_label", "optional": true, "type": "String", "list": true, "value-key": "PARTICIPANT_LABEL"}, {"command-line-flag": "--session_label", "description": "The label(s) of the session that should be analyzed. The label corresponds to ses-<participant_label> from the BIDS spec (so it does not include \"ses-\"). If this parameter is not provided all sessions should be analyzed. Multiple sessions can be specified with a space separated list.", "id": "session_label", "name": "session_label", "optional": true, "type": "String", "list": true, "value-key": "SESSION_LABEL"}, {"command-line-flag": "--bucket", "description": "The name of an S3 bucket which holds BIDS organized data. You must have built your bucket with credentials to the S3 bucket you wish to access.", "id": "bucket", "name": "bucket", "optional": true, "type": "String", "value-key": "BUCKET"}, {"command-line-flag": "--remote_path", "description": "The path to the data on your S3 bucket. The data will be downloaded to the provided bids_dir on your machine.", "id": "remote_path", "name": "remote_path", "optional": true, "type": "String", "value-key": "REMOTE_PATH"}, {"command-line-flag": "--push_data", "description": "flag to push derivatives back up to S3.", "id": "push_data", "name": "push_data", "optional": true, "type": "Flag", "value-key": "PUSH_DATA"}, {"command-line-flag": "--dataset", "description": "The name of the dataset you are perfoming QC on.", "id": "dataset", "name": "dataset", "optional": true, "type": "String", "value-key": "DATASET"}, {"command-line-flag": "--atlas", "description": "The atlas being analyzed in QC (if you only want one).", "id": "atlas", "name": "atlas", "optional": true, "type": "String", "value-key": "ATLAS"}, {"command-line-flag": "--minimal", "description": "Determines whether to show a minimal or full set of plots.", "id": "minimal", "name": "minimal", "optional": true, "type": "Flag", "value-key": "MINIMAL"}, {"command-line-flag": "--hemispheres", "description": "Whether or not to break degrees into hemispheres or not", "id": "hemispheres", "name": "hemispheres", "optional": true, "type": "Flag", "value-key": "HEMISPHERES"}, {"command-line-flag": "--log", "description": "Determines axis scale for plotting.", "id": "log", "name": "log", "optional": true, "type": "Flag", "value-key": "LOG"}, {"command-line-flag": "--debug", "description": "flag to store temp files along the path of processing.", "id": "debug", "name": "debug", "optional": true, "type": "Flag", "value-key": "DEBUG"}], "name": "BIDS App - ndmg", "outputfiles": [{"id": "output_directory", "name": "BIDS derivatives directory from ndmg", "optional": false, "path-template": "OUTPUT_DIR"}], "suggestedresources": {"cpu-cores": 1, "ram": 12, "walltime-estimate": 7200}, "toolversion": "v0.1.0", "ark_id": "https://n2t.net/ark:/70798/p716mrs5z0kpq6bmfb", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.4687757", "title": "imputePrepSanger", "description": "This pipeline takes genotype files, and adjusts the strand, the positions, the reference alleles, performs quality control steps and output a vcf file that satisfies the requirement for submittion to the Sanger Imputation Service (https://imputation.sanger.ac.uk/) for imputation using the Haplotype Reference Consortim reference panel. The strand files for most genotyping chip can be found on Will Rayner's website (http://www.well.ox.ac.uk/~wrayner/strand/).", "publicationdate": "2021-04-14", "deprecated": false, "downloads": 313, "author": "Greenwood Lab Montreal", "version": "1.0.0", "doi": "10.5281/zenodo.4687757", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["bioinformatics", "genetic"]}, "inputs": [{"default-value": "0.1", "description": "If in an individual the proportion of genotype missing is higher than this parameter, that individual is excluded from the dataset.", "type": "Number", "name": "Maximum per person missing", "value-key": "[MIND]", "id": "mind", "list": false, "optional": false}, {"default-value": "0.1", "description": "If for a SNP the proportion of missing genotype is higher than this parameter, that SNP is excluded from the dataset.", "type": "Number", "name": "Maximum per SNP missing", "value-key": "[GENO]", "id": "geno", "list": false, "optional": false}, {"default-value": "0.05", "description": "If the frequency of the minor allele for a SNP is lower than this parameter, this SNP is excluded from the dataset.", "type": "Number", "name": "Minor allele frequency", "value-key": "[MAF]", "id": "maf", "list": false, "optional": false}, {"default-value": "5e-8", "description": "If, for a SNP, the p-value obtained from a test of Hardy-Weinberg equilibrium is lower than this parameter, the equilibrium hypothesis is rejected and the SNP is excluded from the dataset. ", "type": "Number", "name": "Hardy-Weinberg equilibrium", "value-key": "[HWE]", "id": "hwe", "list": false, "optional": false}, {"name": "Repository with variable inputs", "description": "Repository that contains variable inputs as the *.ped, *.map file, and the *.strand files. The strand file needs to match your genotyping chip, and build 37.", "type": "File", "value-key": "[VAR_DATA]", "id": "var_data", "list": false, "optional": false}, {"default-value": "imputePrepSanger_output", "description": "Output directory name.", "type": "String", "name": "Output directory", "value-key": "[OUTPUT]", "id": "outdir", "list": false, "optional": false}], "toolversion": "1.0.0", "containerimage": {"image": "GreenwoodLab/imputePrepSanger:imputeprepsanger_v1.0", "index": "shub://", "type": "singularity"}, "custom": {"cbrain:author": "Natacha Beck"}, "suggestedresources": {"walltime-estimate": 10000}, "outputfiles": [{"description": "A folder containing the output files", "name": "Output folder", "path-template": "[OUTPUT]", "id": "folder_out", "list": false, "optional": false}], "commandline": "cp /imputePrepSanger/*.awk . || exit 20 ; mkdir -p fix_data || exit 21 ; ln -f -s /fix_data/* fix_data || exit 21 ; test -f [VAR_DATA]/*.ped || ( echo Missing PED file && exit 22 ) ; test -f [VAR_DATA]/*.strand || ( echo Missing STRAND file && exit 23 ) ; pl=$(basename [VAR_DATA]/*.ped .ped) ; st=$(basename [VAR_DATA]/*.strand .strand) ; bash imputePrep_script.sh ${pl} ${st} [MIND] [GENO] [MAF] [HWE] [VAR_DATA] fix_data [OUTPUT]", "name": "imputePrepSanger", "onlineplatformurls": ["https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id=72"], "ark_id": "https://n2t.net/ark:/70798/p795fcvmx52h0632zg", "platforms": [{"img": "/static/img/run_on_cbrain_green.png", "uri": "/cbrainredirect?cbrainurl=https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id%3D72"}]}, {"id": "zenodo.4685127", "title": "ePRS_5HTT", "description": "Run ePRS_5HTT script, for example see https://github.com/SilveiraLab/ePRS/tree/master/example", "publicationdate": "2021-04-14", "deprecated": false, "downloads": 312, "author": "Patricia Pelufo Silveira Lab", "version": "1.0.0", "doi": "10.5281/zenodo.4685127", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["bioinformatics", "genetic"]}, "containerimage": {"type": "singularity", "index": "docker://", "image": "silveiralab/eprs_5htt"}, "onlineplatformurls": ["https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id=294"], "inputs": [{"description": "Gen file", "type": "File", "list": false, "value-key": "[GEN_DATA]", "id": "gen_data", "name": "Gen file", "optional": false}, {"description": "Sample file", "type": "File", "list": false, "value-key": "[SAMPLE_DATA]", "id": "sample_data", "name": "Sample file", "optional": false}], "suggestedresources": {"walltime-estimate": 10000}, "name": "ePRS_5HTT", "commandline": "OUTDIR=$PWD/eprs_score; mkdir -p $OUTDIR || exit 1; run_ePRS_5HTT.sh [GEN_DATA] [SAMPLE_DATA] $OUTDIR > $OUTDIR/trace.log", "custom": {"cbrain:author": "Natacha Beck"}, "outputfiles": [{"path-template": "eprs_score", "description": "A folder containing the output files", "list": false, "id": "folder_out", "name": "Output folder", "optional": false}], "toolversion": "1.0.0", "ark_id": "https://n2t.net/ark:/70798/p7tkwnjfr6qt28zjvs", "platforms": [{"img": "/static/img/run_on_cbrain_green.png", "uri": "/cbrainredirect?cbrainurl=https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id%3D294"}]}, {"id": "zenodo.4767416", "title": "MSSeg example method", "description": "Detect new MS lesions from two FLAIR images.", "publicationdate": "2021-05-17", "deprecated": false, "downloads": 144, "author": "Arthur Masson", "version": "v0.1.3", "doi": "10.5281/zenodo.4767416", "schemaversion": "0.5", "container": "docker", "tags": {"purpose": "test MSSeg example method", "status": "example"}, "name": "MSSeg example method", "toolversion": "v0.1.3", "commandline": "python process.py -t1 [FLAIR1] -t2 [FLAIR2] -o [SEGMENTATION]", "containerimage": {"image": "arthurmassoninria/msseg-example:latest", "index": "hub.docker.com", "type": "docker", "container-opts": ["--gpus", "all"]}, "inputs": [{"id": "flair_time01", "name": "The first flair image (e.g. flair_time01.nii.gz)", "optional": false, "type": "File", "value-key": "[FLAIR1]"}, {"id": "flair_time02", "name": "The second flair image (e.g. flair_time02.nii.gz)", "optional": false, "type": "File", "value-key": "[FLAIR2]"}, {"id": "output_segmentation", "name": "The output segmentation path (e.g. segmentation.nii.gz)", "optional": false, "type": "File", "value-key": "[SEGMENTATION]"}], "outputfiles": [{"id": "segmentation", "name": "The segmentation output", "optional": false, "path-template": "[SEGMENTATION]"}], "suggestedresources": {"cpu-cores": 1, "ram": 1, "walltime-estimate": 60}, "errorcodes": [{"code": 1, "description": "Crashed"}], "ark_id": "https://n2t.net/ark:/70798/p7r94fv8s32ff2tmf8", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.4769977", "title": "MSSeg Example Method CPU", "description": "Detect new MS lesions from two FLAIR images.", "publicationdate": "2021-05-18", "deprecated": false, "downloads": 142, "author": "Arthur Masson", "version": "v0.1.3", "doi": "10.5281/zenodo.4769977", "schemaversion": "0.5", "container": "docker", "tags": {"purpose": "test MSSeg example method", "status": "example"}, "name": "MSSeg Example Method CPU", "toolversion": "v0.1.3", "commandline": "python /nnunet/process.py -t1 [FLAIR1] -t2 [FLAIR2] -o [SEGMENTATION]", "containerimage": {"image": "arthurmassoninria/msseg-cpu-example:latest", "index": "hub.docker.com", "type": "docker"}, "inputs": [{"id": "flair_time01", "name": "The first flair image (e.g. flair_time01.nii.gz)", "optional": false, "type": "File", "value-key": "[FLAIR1]"}, {"id": "flair_time02", "name": "The second flair image (e.g. flair_time02.nii.gz)", "optional": false, "type": "File", "value-key": "[FLAIR2]"}, {"id": "output_segmentation", "name": "The output segmentation path (e.g. segmentation.nii.gz)", "optional": false, "type": "File", "value-key": "[SEGMENTATION]"}], "outputfiles": [{"id": "segmentation", "name": "The segmentation output", "optional": false, "path-template": "[SEGMENTATION]"}], "suggestedresources": {"cpu-cores": 1, "ram": 1, "walltime-estimate": 60}, "errorcodes": [{"code": 1, "description": "Crashed"}], "ark_id": "https://n2t.net/ark:/70798/p7zq8w0hx1zpm6jfg4", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.4778224", "title": "MSSeg_Example_Method_GPU", "description": "Detect new MS lesions from two FLAIR images.", "publicationdate": "2021-05-21", "deprecated": false, "downloads": 139, "author": "Arthur Masson", "version": "v0.1.3", "doi": "10.5281/zenodo.4778224", "schemaversion": "0.5", "container": "docker", "tags": {"purpose": "test MSSeg example method", "status": "example"}, "name": "MSSeg_Example_Method_GPU", "toolversion": "v0.1.3", "commandline": "python /nnunet/process.py -t1 [FLAIR1] -t2 [FLAIR2] -o [SEGMENTATION]", "containerimage": {"image": "arthurmassoninria/msseg-example:latest", "index": "hub.docker.com", "type": "docker", "container-opts": ["--gpus", "all"]}, "inputs": [{"id": "flair_time01", "name": "The first flair image (e.g. flair_time01.nii.gz)", "optional": false, "type": "File", "value-key": "[FLAIR1]"}, {"id": "flair_time02", "name": "The second flair image (e.g. flair_time02.nii.gz)", "optional": false, "type": "File", "value-key": "[FLAIR2]"}, {"id": "output_segmentation", "name": "The output segmentation path (e.g. segmentation.nii.gz)", "optional": false, "type": "String", "value-key": "[SEGMENTATION]"}], "outputfiles": [{"id": "segmentation", "name": "The segmentation output", "optional": false, "path-template": "[SEGMENTATION]"}], "ark_id": "https://n2t.net/ark:/70798/p7dtmjvts13cz61g9k", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.4778170", "title": "MSSeg_Example_Method_CPU", "description": "Detect new MS lesions from two FLAIR images.", "publicationdate": "2021-05-21", "deprecated": false, "downloads": 136, "author": "Arthur Masson", "version": "v0.1.4", "doi": "10.5281/zenodo.4778170", "schemaversion": "0.5", "container": "docker", "tags": {"purpose": "test MSSeg example method", "status": "example"}, "name": "MSSeg_Example_Method_CPU", "toolversion": "v0.1.4", "commandline": "python /nnunet/process.py -t1 [FLAIR1] -t2 [FLAIR2] -o [SEGMENTATION]", "containerimage": {"image": "arthurmassoninria/msseg-cpu-example:latest", "index": "hub.docker.com", "type": "docker"}, "inputs": [{"id": "flair_time01", "name": "The first flair image (e.g. flair_time01.nii.gz)", "optional": false, "type": "File", "value-key": "[FLAIR1]"}, {"id": "flair_time02", "name": "The second flair image (e.g. flair_time02.nii.gz)", "optional": false, "type": "File", "value-key": "[FLAIR2]"}, {"id": "output_segmentation", "name": "The output segmentation (e.g. segmentation.nii.gz)", "optional": false, "type": "String", "value-key": "[SEGMENTATION]"}], "outputfiles": [{"id": "segmentation", "name": "The segmentation output", "optional": false, "path-template": "[SEGMENTATION]"}], "ark_id": "https://n2t.net/ark:/70798/p7rd424nm1wc12s9jr", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.4897778", "title": "Longiseg", "description": "Detect new MS lesions from two FLAIR images.", "publicationdate": "2021-06-03", "deprecated": false, "downloads": 72, "author": "Arthur Masson", "version": "v0.1.1", "doi": "10.5281/zenodo.4897778", "schemaversion": "0.5", "container": "docker", "tags": {"purpose": "longiseg method"}, "name": "Longiseg", "toolversion": "v0.1.1", "commandline": "python /longiseg/process.py -t1 [FLAIR1] -t2 [FLAIR2] -o [SEGMENTATION]", "containerimage": {"image": "arthurmassoninria/longiseg:latest", "index": "hub.docker.com", "type": "docker", "container-opts": ["--gpus", "all"]}, "inputs": [{"id": "flair_time01", "name": "The first flair image (e.g. flair_time01.nii.gz)", "optional": false, "type": "File", "value-key": "[FLAIR1]"}, {"id": "flair_time02", "name": "The second flair image (e.g. flair_time02.nii.gz)", "optional": false, "type": "File", "value-key": "[FLAIR2]"}, {"id": "output_segmentation", "name": "The output segmentation (e.g. segmentation.nii.gz)", "optional": false, "type": "String", "value-key": "[SEGMENTATION]"}], "outputfiles": [{"id": "segmentation", "name": "The segmentation output", "optional": false, "path-template": "[SEGMENTATION]"}], "ark_id": "https://n2t.net/ark:/70798/p72pw2hsg584s4dm9v", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.6139903", "title": "fsl_bet-test", "description": "Automated brain extraction tool for FSL", "publicationdate": "2022-02-18", "deprecated": false, "downloads": 67, "author": "Sandesh PATIL", "version": "1.0.0", "doi": "10.5281/zenodo.6139903", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "mri"]}, "commandline": "bet [INPUT_FILE] [MASK] [FRACTIONAL_INTENSITY] [VERTICAL_GRADIENT] [CENTER_OF_GRAVITY] [OVERLAY_FLAG] [BINARY_MASK_FLAG] [APPROX_SKULL_FLAG] [NO_SEG_OUTPUT_FLAG] [VTK_VIEW_FLAG] [HEAD_RADIUS] [THRESHOLDING_FLAG] [ROBUST_ITERS_FLAG] [RES_OPTIC_CLEANUP_FLAG] [REDUCE_BIAS_FLAG] [SLICE_PADDING_FLAG] [MASK_WHOLE_SET_FLAG] [ADD_SURFACES_FLAG] [ADD_SURFACES_T2] [VERBOSE_FLAG] [DEBUG_FLAG]", "containerimage": {"image": "mcin/docker-fsl:latest", "index": "index.docker.io", "type": "docker"}, "descriptorurl": "https://github.com/aces/cbrain-plugins-neuro/blob/master/cbrain_task_descriptors/fsl_bet.json", "groups": [{"description": "Specify parameters that alter the default BET functionality", "id": "optional_params_group", "members": ["fractional_intensity", "vg_fractional_intensity", "center_of_gravity", "overlay_flag", "binary_mask_flag", "approx_skull_flag", "no_seg_output_flag", "vtk_mesh", "head_radius", "thresholding_flag"], "name": "Main Program Parameters"}, {"description": "Mutually exclusive options that specify variations on how BET should be run.", "id": "variational_params_group", "members": ["robust_iters_flag", "residual_optic_cleanup_flag", "reduce_bias_flag", "slice_padding_flag", "whole_set_mask_flag", "additional_surfaces_flag", "additional_surfaces_t2"], "mutually-exclusive": true, "name": "Variations on Default Functionality"}, {"description": "Optional miscellaneous parameters when running BET", "id": "miscellaneous_params_group", "members": ["verbose_flag", "debug_flag"], "name": "Miscellaneous Parameters"}], "inputs": [{"description": "Input image (e.g. img.nii.gz)", "id": "infile", "name": "Input file", "optional": false, "type": "File", "value-key": "[INPUT_FILE]"}, {"description": "Output brain mask (e.g. img_bet.nii.gz)", "id": "maskfile", "name": "Mask file", "optional": false, "type": "String", "value-key": "[MASK]"}, {"command-line-flag": "-f", "description": "Fractional intensity threshold (0->1); default=0.5; smaller values give larger brain outline estimates", "id": "fractional_intensity", "integer": false, "maximum": 1, "minimum": 0, "name": "Fractional intensity threshold", "optional": true, "type": "Number", "value-key": "[FRACTIONAL_INTENSITY]"}, {"command-line-flag": "-g", "description": "Vertical gradient in fractional intensity threshold (-1->1); default=0; positive values give larger brain outline at bottom, smaller at top", "id": "vg_fractional_intensity", "integer": false, "maximum": 1, "minimum": -1, "name": "Vertical gradient fractional intensity threshold", "optional": true, "type": "Number", "value-key": "[VERTICAL_GRADIENT]"}, {"command-line-flag": "-c", "description": "The xyz coordinates of the center of gravity (voxels, not mm) of initial mesh surface. Must have exactly three numerical entries in the list (3-vector).", "id": "center_of_gravity", "list": true, "max-list-entries": 3, "min-list-entries": 3, "name": "Center of gravity vector", "optional": true, "type": "Number", "value-key": "[CENTER_OF_GRAVITY]"}, {"command-line-flag": "-o", "description": "Generate brain surface outline overlaid onto original image", "id": "overlay_flag", "name": "Overlay flag", "optional": true, "type": "Flag", "value-key": "[OVERLAY_FLAG]"}, {"command-line-flag": "-m", "description": "Generate binary brain mask", "id": "binary_mask_flag", "name": "Binary mask flag", "optional": true, "type": "Flag", "value-key": "[BINARY_MASK_FLAG]"}, {"command-line-flag": "-s", "description": "Generate rough skull image (not as clean as betsurf)", "id": "approx_skull_flag", "name": "Approximate skull flag", "optional": true, "type": "Flag", "value-key": "[APPROX_SKULL_FLAG]"}, {"command-line-flag": "-n", "description": "Don't generate segmented brain image output", "id": "no_seg_output_flag", "name": "No segmented brain image flag", "optional": true, "type": "Flag", "value-key": "[NO_SEG_OUTPUT_FLAG]"}, {"command-line-flag": "-e", "description": "Generate brain surface as mesh in .vtk format", "id": "vtk_mesh", "name": "VTK format brain surface mesh flag", "optional": true, "type": "Flag", "value-key": "[VTK_VIEW_FLAG]"}, {"command-line-flag": "-r", "description": "head radius (mm not voxels); initial surface sphere is set to half of this", "id": "head_radius", "name": "Head Radius", "optional": true, "type": "Number", "value-key": "[HEAD_RADIUS]"}, {"command-line-flag": "-t", "description": "Apply thresholding to segmented brain image and mask", "id": "thresholding_flag", "name": "Threshold segmented image flag", "optional": true, "type": "Flag", "value-key": "[THRESHOLDING_FLAG]"}, {"command-line-flag": "-R", "description": "More robust brain center estimation, by iterating BET with a changing center-of-gravity.", "id": "robust_iters_flag", "name": "Robust iterations flag", "optional": true, "type": "Flag", "value-key": "[ROBUST_ITERS_FLAG]"}, {"command-line-flag": "-S", "description": "This attempts to cleanup residual eye and optic nerve voxels which bet2 can sometimes leave behind. This can be useful when running SIENA or SIENAX, for example. Various stages involving standard-space masking, morphpological operations and thresholdings are combined to produce a result which can often give better results than just running bet2.", "id": "residual_optic_cleanup_flag", "name": "Residual optic cleanup flag", "optional": true, "type": "Flag", "value-key": "[RES_OPTIC_CLEANUP_FLAG]"}, {"command-line-flag": "-B", "description": "This attempts to reduce image bias, and residual neck voxels. This can be useful when running SIENA or SIENAX, for example. Various stages involving FAST segmentation-based bias field removal and standard-space masking are combined to produce a result which can often give better results than just running bet2.", "id": "reduce_bias_flag", "name": "Bias reduction flag", "optional": true, "type": "Flag", "value-key": "[REDUCE_BIAS_FLAG]"}, {"command-line-flag": "-Z", "description": "This can improve the brain extraction if only a few slices are present in the data (i.e., a small field of view in the Z direction). This is achieved by padding the end slices in both directions, copying the end slices several times, running bet2 and then removing the added slices.", "id": "slice_padding_flag", "name": "Slice padding flag", "optional": true, "type": "Flag", "value-key": "[SLICE_PADDING_FLAG]"}, {"command-line-flag": "-F", "description": "This option uses bet2 to determine a brain mask on the basis of the first volume in a 4D data set, and applies this to the whole data set. This is principally intended for use on FMRI data, for example to remove eyeballs. Because it is normally important (in this application) that masking be liberal (ie that there be little risk of cutting out valid brain voxels) the -f threshold is reduced to 0.3, and also the brain mask is \"dilated\" slightly before being used.", "id": "whole_set_mask_flag", "name": "Mask-whole-set flag", "optional": true, "type": "Flag", "value-key": "[MASK_WHOLE_SET_FLAG]"}, {"command-line-flag": "-A", "description": "This runs both bet2 and betsurf programs in order to get the additional skull and scalp surfaces created by betsurf. This involves registering to standard space in order to allow betsurf to find the standard space masks it needs.", "id": "additional_surfaces_flag", "name": "Additional surfaces flag", "optional": true, "type": "Flag", "value-key": "[ADD_SURFACES_FLAG]"}, {"command-line-flag": "-A2", "description": "This is the same as -A except that a T2 image is also input, to further improve the estimated skull and scalp surfaces. As well as carrying out the standard space registration this also registers the T2 to the T1 input image.", "id": "additional_surfaces_t2", "name": "Additional surfaces with T2", "optional": true, "type": "File", "value-key": "[ADD_SURFACES_T2]"}, {"command-line-flag": "-v", "description": "Switch on diagnostic messages", "id": "verbose_flag", "name": "Verbose Flag", "optional": true, "type": "Flag", "value-key": "[VERBOSE_FLAG]"}, {"command-line-flag": "-d", "description": "Don't delete temporary intermediate images", "id": "debug_flag", "name": "Debug Flag", "optional": true, "type": "Flag", "value-key": "[DEBUG_FLAG]"}], "name": "fsl_bet-test", "outputfiles": [{"description": "Main default mask output of BET", "id": "outfile", "name": "Output mask file", "optional": true, "path-template": "[MASK].nii.gz"}, {"description": "Binary mask file (from -m option)", "id": "binary_mask", "name": "Output binary mask file", "optional": true, "path-template": "[MASK]_mask.nii.gz"}, {"description": "Overlaid brain surface onto original image", "id": "overlay_file", "name": "Surface overlay file", "optional": true, "path-template": "[MASK]_overlay.nii.gz"}, {"description": "Approximate skull image file", "id": "approx_skull_img", "name": "Approximate skull file", "optional": true, "path-template": "[MASK]_skull.nii.gz"}, {"description": "Mesh in VTK format", "id": "output_vtk_mesh", "name": "VTK mesh", "optional": true, "path-template": "[MASK]_mesh.vtk"}, {"description": "Output mask for skull image", "id": "skull_mask", "name": "Skull mask image", "optional": true, "path-template": "[MASK]_skull_mask.nii.gz"}, {"description": "The in-skull mask file from betsurf (from -A or -A2)", "id": "out_inskull_mask", "name": "Output in-skull mask file", "optional": true, "path-template": "[MASK]_inskull_mask.nii.gz"}, {"description": "The in-skull mesh file from betsurf (from -A or -A2)", "id": "out_inskull_mesh", "name": "Output in-skull mesh file", "optional": true, "path-template": "[MASK]_inskull_mesh.nii.gz"}, {"description": "The in-skull mesh .off file from betsurf (from -A or -A2)", "id": "out_inskull_off", "name": "Output in-skull mesh off file", "optional": true, "path-template": "[MASK]_inskull_mesh.off"}, {"description": "The out-skin mask file from betsurf (from -A or -A2)", "id": "out_outskin_mask", "name": "Output out-skin mask file", "optional": true, "path-template": "[MASK]_outskin_mask.nii.gz"}, {"description": "The out-skin mesh file from betsurf (from -A or -A2)", "id": "out_outskin_mesh", "name": "Output out-skin mesh file", "optional": true, "path-template": "[MASK]_outskin_mesh.nii.gz"}, {"description": "The out-skin mesh .off file from betsurf (from -A or -A2)", "id": "out_outskin_off", "name": "Output out-skin mesh off file", "optional": true, "path-template": "[MASK]_outskin_mesh.off"}, {"description": "The out-skull mask file from betsurf (from -A or -A2)", "id": "out_outskull_mask", "name": "Output out-skull mask file", "optional": true, "path-template": "[MASK]_outskull_mask.nii.gz"}, {"description": "The out-skull mesh file from betsurf (from -A or -A2)", "id": "out_outskull_mesh", "name": "Output out-skull mesh file", "optional": true, "path-template": "[MASK]_outskull_mesh.nii.gz"}, {"description": "The out-skull mesh .off file from betsurf (from -A or -A2)", "id": "out_outskull_off", "name": "Output out-skull mesh off file", "optional": true, "path-template": "[MASK]_outskull_mesh.off"}], "tests": [{"assertions": {"exit-code": 0, "output-files": [{"id": "outfile", "md5-reference": "053507dd8605d62f5ba71dbecece17f8"}]}, "invocation": {"infile": "sub-01_T1w.nii.gz", "maskfile": "img_bet"}, "name": "fsl_bet_test"}], "toolversion": "1.0.0", "ark_id": "https://n2t.net/ark:/70798/p7c73wxzc9v6k8b09r", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.4913239", "title": "Longiseg_CPU", "description": "Detect new MS lesions from two FLAIR images (CPU version).", "publicationdate": "2021-06-08", "deprecated": false, "downloads": 57, "author": "Arthur Masson", "version": "v0.1.1", "doi": "10.5281/zenodo.4913239", "schemaversion": "0.5", "container": "docker", "tags": {"purpose": "longiseg method"}, "name": "Longiseg_CPU", "toolversion": "v0.1.1", "commandline": "python /longiseg/process.py -t1 [FLAIR1] -t2 [FLAIR2] -o [SEGMENTATION]", "containerimage": {"image": "arthurmassoninria/longiseg-cpu:latest", "index": "hub.docker.com", "type": "docker"}, "inputs": [{"id": "flair_time01", "name": "The first flair image (e.g. flair_time01.nii.gz)", "optional": false, "type": "File", "value-key": "[FLAIR1]"}, {"id": "flair_time02", "name": "The second flair image (e.g. flair_time02.nii.gz)", "optional": false, "type": "File", "value-key": "[FLAIR2]"}, {"id": "output_segmentation", "name": "The output segmentation (e.g. segmentation.nii.gz)", "optional": false, "type": "String", "value-key": "[SEGMENTATION]"}], "outputfiles": [{"id": "segmentation", "name": "The segmentation output", "optional": false, "path-template": "[SEGMENTATION]"}], "ark_id": "https://n2t.net/ark:/70798/p79sjxx0x5npx8gwwc", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.5885964", "title": "fNIRS Apps: Scalp Coupling Index", "description": "Compute Scalp Coupling Index and mark BIDS status", "publicationdate": "2022-01-21", "deprecated": false, "downloads": 53, "author": "Robert Luke", "version": "v0.3.5", "doi": "10.5281/zenodo.5885964", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroimaging", "fnirs", "quality", "bids"]}, "name": "fNIRS Apps: Scalp Coupling Index", "toolversion": "v0.3.5", "commandline": "/run.py [InputDataset] [SubjectLabel] [SessionLabel] [TaskLabel] [Threshold] [HighFrequency] [HighFrequencyBandwidth]", "containerimage": {"image": "ghcr.io/rob-luke/fnirs-apps-scalp-coupling-index/app:v0.3.5", "index": "ghcr.io", "type": "docker", "entrypoint": true}, "inputs": [{"command-line-flag": "--input-datasets", "id": "input_datasets", "description": "The directory with the input dataset formatted according to the BIDS standard.", "name": "input-datasets", "optional": true, "type": "File", "value-key": "[InputDataset]"}, {"command-line-flag": "--subject-label", "description": "The label(s) of the subjects(s) that should be analyzed. The label corresponds to sub-<subject_label> from the BIDS spec (so it does not include \"sub-\"). If this parameter is not provided all subjects should be analyzed. Multiple participants can be specified with a space separated list.", "id": "subject_label", "name": "subject-label", "optional": true, "type": "String", "list": true, "value-key": "[SubjectLabel]"}, {"command-line-flag": "--session-label", "description": "The label(s) of the session(s) that should be analyzed. The label corresponds to ses-<session_label> from the BIDS spec (so it does not include \"ses-\"). If this parameter is not provided all sessions should be analyzed. Multiple sessions can be specified with a space separated list.", "id": "session_label", "name": "session-label", "optional": true, "type": "String", "list": true, "value-key": "[SessionLabel]"}, {"command-line-flag": "--task-label", "description": "The label(s) of the tasks(s) that should be analyzed. The label corresponds to task-<subject_label> from the BIDS spec. If this parameter is not provided all tasks should be analyzed. Multiple tasks can be specified with a space separated list.", "id": "task_label", "name": "task-label", "optional": true, "type": "String", "list": true, "value-key": "[TaskLabel]"}, {"command-line-flag": "--threshold", "id": "threshold", "name": "threshold", "optional": true, "type": "Number", "value-key": "[Threshold]"}, {"command-line-flag": "--h-freq", "id": "h_freq", "name": "h-freq", "optional": true, "type": "Number", "value-key": "[HighFrequency]"}, {"command-line-flag": "--h-trans-bandwidth", "id": "h_trans_bandwidth", "name": "h-trans-bandwidth", "optional": true, "type": "Number", "value-key": "[HighFrequencyBandwidth]"}], "outputfiles": [{"id": "output_directory", "name": "BIDS derivatives directory", "optional": false, "path-template": "[InputDataset]"}], "suggestedresources": {"cpu-cores": 1, "ram": 1, "walltime-estimate": 60}, "errorcodes": [{"code": 1, "description": "Crashed"}], "custom": {"BIDSAppSpecVersion": "Draft"}, "ark_id": "https://n2t.net/ark:/70798/p7hb3gzx58xf32fbdq", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.5886927", "title": "fNIRS Apps: GLM Pipeline", "description": "A GLM pipeline for fNIRS data", "publicationdate": "2022-01-21", "deprecated": false, "downloads": 51, "author": "Robert Luke", "version": "v0.3.4", "doi": "10.5281/zenodo.5886927", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroimaging", "fnirs", "glm", "bids"]}, "name": "fNIRS Apps: GLM Pipeline", "toolversion": "v0.3.4", "commandline": "/run.py [InputDataset] [OutputLocation] [SubjectLabel] [SessionLabel] [TaskLabel] [ShortRegression] [ExportDrifts] [ExportShorts] [SampleRate]", "containerimage": {"image": "ghcr.io/rob-luke/fnirs-apps-glm-pipeline/app:v0.3.4", "index": "ghcr.io", "type": "docker", "entrypoint": true}, "inputs": [{"command-line-flag": "--input-datasets", "id": "input_datasets", "description": "The directory with the input dataset formatted according to the BIDS standard.", "name": "input-datasets", "optional": true, "type": "File", "value-key": "[InputDataset]"}, {"command-line-flag": "--output-location", "id": "output_location", "description": "The directory where the output files should be stored.", "name": "output-location", "optional": true, "type": "File", "value-key": "[OutputLocation]"}, {"command-line-flag": "--subject-label", "description": "The label(s) of the subjects(s) that should be analyzed. The label corresponds to sub-<subject_label> from the BIDS spec (so it does not include \"sub-\"). If this parameter is not provided all subjects should be analyzed. Multiple participants can be specified with a space separated list.", "id": "subject_label", "name": "subject-label", "optional": true, "type": "String", "list": true, "value-key": "[SubjectLabel]"}, {"command-line-flag": "--session-label", "description": "The label(s) of the session(s) that should be analyzed. The label corresponds to ses-<session_label> from the BIDS spec (so it does not include \"ses-\"). If this parameter is not provided all sessions should be analyzed. Multiple sessions can be specified with a space separated list.", "id": "session_label", "name": "session-label", "optional": true, "type": "String", "list": true, "value-key": "[SessionLabel]"}, {"command-line-flag": "--task-label", "description": "The label(s) of the tasks(s) that should be analyzed. The label corresponds to task-<subject_label> from the BIDS spec. If this parameter is not provided all tasks should be analyzed. Multiple tasks can be specified with a space separated list.", "id": "task_label", "name": "task-label", "optional": true, "type": "String", "list": true, "value-key": "[TaskLabel]"}, {"command-line-flag": "--short-regression", "id": "short_regression", "name": "short-regression", "optional": true, "type": "String", "value-choices": ["True", "False"], "value-key": "[ShortRegression]"}, {"command-line-flag": "--export-drifts", "id": "export_drifts", "name": "export-drifts", "optional": true, "type": "String", "value-choices": ["True", "False"], "value-key": "[ExportDrifts]"}, {"command-line-flag": "--export-shorts", "id": "export_shorts", "name": "export-shorts", "optional": true, "type": "String", "value-choices": ["True", "False"], "value-key": "[ExportShorts]"}, {"command-line-flag": "--sample-rate", "id": "sample_rate", "name": "sample-rate", "optional": true, "type": "Number", "value-key": "[SampleRate]"}], "outputfiles": [{"id": "output_directory", "name": "BIDS derivatives directory", "optional": false, "path-template": "[OutputLocation]"}], "suggestedresources": {"cpu-cores": 1, "ram": 1, "walltime-estimate": 60}, "errorcodes": [{"code": 1, "description": "Crashed"}], "custom": {"BIDSAppSpecVersion": "Draft"}, "ark_id": "https://n2t.net/ark:/70798/p7zfpcpw5576q8mx3h", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.6881412", "title": "SPM batch", "description": "Run a batch with SPM12", "publicationdate": "2022-07-22", "deprecated": false, "downloads": 44, "author": "Tristan Glatard", "version": "r7771", "doi": "10.5281/zenodo.6881412", "schemaversion": "0.5", "container": "docker", "tags": {"domain": "neuroimaging", "toolbox": "SPM"}, "name": "SPM batch", "toolversion": "r7771", "commandline": "(Xvfb :99 -nolisten tcp -nolisten unix & export DISPLAY=:99) && (cd /spm12-r7771 && octave -W [SPM_BATCH_FILE] &>[LOG_FILE])", "containerimage": {"image": "glatard/spm-octave-5.2.0", "index": "docker://", "type": "docker"}, "inputs": [{"id": "spm_batch_file", "name": "SPM batch file", "type": "File", "value-key": "[SPM_BATCH_FILE]"}, {"id": "log_file_name", "name": "Name of output log file (stdout & stderr)", "optional": true, "default-value": "batch.log", "type": "String", "value-key": "[LOG_FILE]"}], "outputfiles": [{"id": "log_file", "name": "Log file (stdout & stderr)", "optional": false, "path-template": "[LOG_FILE]"}], "ark_id": "https://n2t.net/ark:/70798/p7rz1n06h9bx40ndtt", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7738457", "title": "FreeSurfer-Recon-all_v5", "description": "Performs all, or any part of, the FreeSurfer cortical reconstruction process (https://surfer.nmr.mgh.harvard.edu/fswiki/recon-all).", "publicationdate": "2023-03-15", "deprecated": false, "downloads": 43, "author": "Laboratory for Computational Neuroimaging ", "version": "v5.3", "doi": "10.5281/zenodo.7738457", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "suggestedresources": {"ram": 10240, "walltime-estimate": 960, "cpu-cores": 1}, "outputfiles": [{"name": "Output", "optional": false, "description": "The subject data upon which to operate ", "id": "subjid_output", "path-template": "[SUBJID]"}], "name": "FreeSurfer-Recon-all_v5", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_5.3", "type": "singularity"}, "toolversion": "v5.3", "commandline": "export SUBJECTS_DIR=`pwd`; recon-all [SUBJID] [INPUT] [DIRECTIVES] [QCACHE] [MPRAGE] [3T] [CW256] [NOTAL-CHECK] [HYPPOCAMPAL-SUBFIELDS] [BRAINSTEM-STRUCTURES] [NO-WSGCAATLAS] [NO-SKULLSTRIP]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "Output name", "command-line-flag": "-subjid", "optional": false, "value-key": "[SUBJID]", "type": "String", "id": "subjid"}, {"name": "NIFTI file", "id": "input", "optional": false, "value-key": "[INPUT]", "description": "Single NIFTI file from series.", "command-line-flag": "-i", "type": "File"}, {"name": "Directive", "default-value": "-all", "value-key": "[DIRECTIVES]", "optional": false, "type": "String", "id": "directives", "value-choices": ["-all", "-autorecon1", "-autorecon2", "-autorecon2-cp", "-autorecon2-wm", "-autorecon2-inflate1", "-autorecon2-perhemi", "-autorecon3"]}, {"name": "qcache", "id": "qcache_flag", "optional": true, "value-key": "[QCACHE]", "description": "Produce the pre-cached files required by the Qdec utility, allowing rapid analysis of group data.", "command-line-flag": "-qcache", "type": "Flag"}, {"name": "mprage", "id": "mprage_flag", "optional": true, "value-key": "[MPRAGE]", "description": "Assume scan parameters are MGH MP-RAGE protocol.", "command-line-flag": "-mprage", "type": "Flag"}, {"name": "3T", "id": "3T_flag", "optional": true, "value-key": "[3T]", "description": "The -3T flag enables two specific options in recon-all for images acquired with a 3T scanner:  3T-specific NU intensity correction parameters are used in the Non-Uniform normalization stage, and the Schwartz 3T atlas is used for Talairach alignment", "command-line-flag": "-3T", "type": "Flag"}, {"name": "cw256", "id": "cw256_flag", "optional": true, "value-key": "[CW256]", "description": "Include this flag after -autorecon1 if images have a FOV > 256.", "command-line-flag": "-cw256", "type": "Flag"}, {"name": "Notal check", "id": "notal_flag", "optional": true, "value-key": "[NOTAL-CHECK]", "description": "Skip the automatic failure detection of Talairach alignment.", "command-line-flag": "-notal-check", "type": "Flag"}, {"name": "Hippocampal-subfileds-T1", "id": "hippocampal_subfields_T1_flag", "optional": true, "value-key": "[HYPPOCAMPAL-SUBFIELDS]", "description": "Segmentation of hippocampal subfields using input T1 scan.", "command-line-flag": "-hippocampal-subfields-T1", "type": "Flag"}, {"name": "Brainstem Structures", "id": "brainstem_structures_flag", "optional": true, "value-key": "[BRAINSTEM-STRUCTURES]", "description": "Segmentation of brainstem structures.", "command-line-flag": "-brainstem-structures", "type": "Flag"}, {"name": "No wsgcaatlas", "id": "no_wsgcaatlas_flag", "optional": true, "value-key": "[NO-WSGCAATLAS]", "description": "Do not use GCA atlas when skull stripping.", "command-line-flag": "-no-wsgcaatlas", "type": "Flag"}, {"name": "No skull strip", "id": "noskullstrip_flag", "optional": true, "value-key": "[NO-SKULLSTRIP]", "description": "Exclude skull strip step.", "command-line-flag": "-noskullstrip", "type": "Flag"}], "ark_id": "https://n2t.net/ark:/70798/p7n8tmxds29w50bft8", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.6342345", "title": "fNIRS Apps: Quality Reports", "description": "Generate quality reports for fNIRS data", "publicationdate": "2022-03-10", "deprecated": false, "downloads": 42, "author": "Robert Luke", "version": "v0.3.8", "doi": "10.5281/zenodo.6342345", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroimaging", "fnirs", "quality", "bids"]}, "name": "fNIRS Apps: Quality Reports", "toolversion": "v0.3.8", "commandline": "/run.py [InputDataset] [OutputLocation] [SubjectLabel] [SessionLabel] [TaskLabel] [SCIThreshold] [PeakPowerThreshold]", "containerimage": {"image": "ghcr.io/rob-luke/fnirs-apps-quality-reports/app:v0.3.8", "index": "ghcr.io", "type": "docker", "entrypoint": true}, "inputs": [{"command-line-flag": "--input-datasets", "id": "input_datasets", "description": "The directory with the input dataset formatted according to the BIDS standard.", "name": "input-datasets", "optional": true, "type": "File", "value-key": "[InputDataset]"}, {"command-line-flag": "--output-location", "id": "output_location", "description": "The directory where the output files should be stored.", "name": "output-location", "optional": true, "type": "File", "value-key": "[OutputLocation]"}, {"command-line-flag": "--subject-label", "description": "The label(s) of the subjects(s) that should be analyzed. The label corresponds to sub-<subject_label> from the BIDS spec (so it does not include \"sub-\"). If this parameter is not provided all subjects should be analyzed. Multiple participants can be specified with a space separated list.", "id": "subject_label", "name": "subject-label", "optional": true, "type": "String", "list": true, "value-key": "[SubjectLabel]"}, {"command-line-flag": "--session-label", "description": "The label(s) of the session(s) that should be analyzed. The label corresponds to ses-<session_label> from the BIDS spec (so it does not include \"ses-\"). If this parameter is not provided all sessions should be analyzed. Multiple sessions can be specified with a space separated list.", "id": "session_label", "name": "session-label", "optional": true, "type": "String", "list": true, "value-key": "[SessionLabel]"}, {"command-line-flag": "--task-label", "description": "The label(s) of the tasks(s) that should be analyzed. The label corresponds to task-<subject_label> from the BIDS spec. If this parameter is not provided all tasks should be analyzed. Multiple tasks can be specified with a space separated list.", "id": "task_label", "name": "task-label", "optional": true, "type": "String", "list": true, "value-key": "[TaskLabel]"}, {"command-line-flag": "--sci-threshold", "id": "sci_threshold", "name": "sci-threshold", "optional": true, "type": "Number", "value-key": "[SCIThreshold]"}, {"command-line-flag": "--pp-threshold", "id": "pp_threshold", "name": "pp-threshold", "optional": true, "type": "Number", "value-key": "[PeakPowerThreshold]"}], "outputfiles": [{"id": "output_directory", "name": "BIDS derivatives directory", "optional": false, "path-template": "[OutputLocation]"}], "suggestedresources": {"cpu-cores": 1, "ram": 1, "walltime-estimate": 60}, "errorcodes": [{"code": 1, "description": "Crashed"}], "custom": {"BIDSAppSpecVersion": "Draft"}, "ark_id": "https://n2t.net/ark:/70798/p7qz6pc5t23nh2p8p3", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.5717438", "title": "curve fitting", "description": "Curve fitting tool for pixel intensity over time.", "publicationdate": "2021-11-21", "deprecated": false, "downloads": 37, "author": "Center for Neurological Imaging", "version": "v0.1.0", "doi": "10.5281/zenodo.5717438", "schemaversion": "0.5", "container": "docker", "tags": {}, "name": "curve fitting", "toolversion": "v0.1.0", "commandline": "python3 curve_fitting.py [FILE]", "containerimage": {"image": "curve-fitting/curve-fitting:latest", "index": "docker://", "type": "docker"}, "inputs": [{"id": "inputFile", "name": "Input File", "description": "JSON data file containing pixel intensity values", "optional": false, "type": "String", "value-key": "[FILE]", "command-line-flag": "-f"}], "suggestedresources": {"cpu-cores": 1, "ram": 1, "walltime-estimate": 60}, "ark_id": "https://n2t.net/ark:/70798/p77hqf5nf5g2g214d6", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7435009", "title": "FSL SIENA", "description": "SIENA is a package for both single-time-point (\"cross-sectional\") and two-time-point (\"longitudinal\") analysis of brain change, in particular, the estimation of atrophy (volumetric loss of brain tissue)", "publicationdate": "2022-12-13", "deprecated": false, "downloads": 36, "author": "Oxford Centre for Functional MRI of the Brain (FMRIB)", "version": "6.0.4", "doi": "10.5281/zenodo.7435009", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["neuroimaging", "mri", "fmri"], "toolbox": "fsl"}, "name": "FSL SIENA", "toolversion": "6.0.4", "commandline": "/opt/fsl-6.0.4/bin/siena [INPUT1] [INPUT2] [OUTPUT_DIR] [DEBUG] [BET_OPTS] [TWO_CLASS_SEGMENTATION] [T2_WEIGHTED] [STANDARD_SPACE_MASKING] [IGNORE_UPWARDS] [IGNORE_DOWNWARDS] [SIENA_DIFF_OPTS] [VIENA] [VENTRICLE_MASK_IMAGE]", "containerimage": {"image": "mathdugre/fsl:6.0.4", "index": "docker://", "type": "singularity"}, "inputs": [{"id": "input1", "name": "First T1 weighted image", "optional": false, "type": "String", "value-key": "[INPUT1]"}, {"id": "input2", "name": "Second T1 weighted image", "optional": false, "type": "String", "value-key": "[INPUT2]"}, {"command-line-flag": "-o", "id": "output_dir", "name": "set output directory (default output is <input1>_to_<input2>_siena)", "optional": true, "type": "String", "value-key": "[OUTPUT_DIR]"}, {"command-line-flag": "-d", "id": "debug", "name": "debug (don't delete intermediate files)", "optional": true, "type": "Flag", "value-key": "[DEBUG]"}, {"command-line-flag": "-B", "id": "bet_opts", "name": "options to pass to BET brain extraction (inside double-quotes), e.g. -B \"-f 0.3\"", "optional": true, "type": "String", "value-key": "[BET_OPTS]"}, {"command-line-flag": "-2", "id": "two_class_segmentation", "name": "two-class segmentation (don't segment grey and white matter separately)", "optional": true, "type": "Flag", "value-key": "[TWO_CLASS_SEGMENTATION]"}, {"command-line-flag": "-t2", "id": "t2_weighted", "name": "T2-weighted input image (default T1-weighted)", "optional": true, "type": "Flag", "value-key": "[T2_WEIGHTED]"}, {"command-line-flag": "-m", "id": "standard_space_masking", "name": "use standard-space masking as well as BET", "optional": true, "type": "Flag", "value-key": "[STANDARD_SPACE_MASKING]"}, {"command-line-flag": "-t", "id": "ignore_upwards", "name": "ignore from t (mm) upwards in MNI152/Talairach space", "optional": true, "type": "Number", "value-key": "[IGNORE_UPWARDS]"}, {"command-line-flag": "-b", "id": "ignore_downwards", "name": "ignore from b (mm) downwards in MNI152/Talairach space (b should probably be negative)", "optional": true, "type": "Number", "value-key": "[IGNORE_DOWNWARDS]"}, {"command-line-flag": "-S", "id": "siena_diff_opts", "name": "options to pass to siena_diff timepoint differencing (inside double-quotes), e.g. -S \"-s -i 20\"", "optional": true, "type": "String", "value-key": "[SIENA_DIFF_OPTS]"}, {"command-line-flag": "-V", "id": "viena", "name": "run ventricle analysis (VIENA)", "optional": true, "type": "Flag", "value-key": "[VIENA]"}, {"command-line-flag": "-v", "id": "ventricle_mask_image", "name": "optional user-supplied ventricle mask (default is /opt/fsl-6.0.4/data/standard/MNI152_T1_2mm_VentricleMask)", "optional": true, "type": "String", "value-key": "[VENTRICLE_MASK_IMAGE]"}], "outputfiles": [{"id": "output1", "name": "Output directory", "optional": false, "path-template": "[OUTPUT_DIR]"}], "ark_id": "https://n2t.net/ark:/70798/p7bj1jzd095vz210ws", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7041445", "title": "HarMNqEEG boutique descriptor", "description": "This toolbox extends frequency domain quantitative electroencephalography (qEEG) methods pursuing higher sensitivity to detect Brain Developmental Disorders. Prior qEEG work lacked integration of cross-spectral information omitting important functional connectivity descriptors. Lack of geographical diversity precluded accounting for site-specific variance, increasing qEEG nuisance variance. We ameliorate these weaknesses by (i) Creating lifespan Riemannian multinational qEEG norms for cross-spectral tensors. These norms result from the HarMNqEEG project fostered by the Global Brain Consortium. We calculated the norms with data from 9 countries, 12 devices, and 14 studies, including 1564 subjects. Developmental equations for the mean and standard deviation of qEEG traditional and Riemannian DPs were calculated using additive mixed-effects models. We demonstrate qEEG \u201cbatch effects\u201d and provide methods to calculate harmonized z-scores. (ii) We also show that harmonized Riemannian norms produce z-scores with increased diagnostic accuracy. These results contribute to developing bias-free, low-cost neuroimaging technologies applicable in various health settings. In this first version, we limited the harmonized qEEG to the 19 channels of the S1020 montage.\nAt the present, the toolbox accepts the input EEG data in EEG-BIDS, EDF+, BDF+, PLG, EEGLAB SET format, and a predefined TEXT format. In the case of not EEG-BIDS structure, the derivatives are stored in the same directory where the raw EEG file is located.\nThe toolbox also contains the definition of the Harmonized qEEG derivatives for the EEG-BIDS format. The derivatives are stored in the BIDS structure compliant with the BIDS definition for the derivatives, in the Hierarchical Data Format (HDF). The functions for creating and loading the HarMNqEEG derivatives can be found in the directory \"derivatives_functions\".\n", "publicationdate": "2022-08-24", "deprecated": false, "downloads": 35, "author": "Eng. Tania Perez Ramirez << tperezdevelopment@gmail.com >> Cuban Center for Neurosciences (https://github.com/tperezdevelopment/HarMNqEEG)", "version": "1.0.0", "doi": "10.5281/zenodo.7041445", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["neuroinformatics", "norms", "eeg"]}, "name": "HarMNqEEG", "toolversion": "1.0.0", "commandline": "HarMNqEEG.sh [generate_cross_spectra] [raw_data_path] [subjects_metadata] [log] [riemlogm] [batch_correction] [FFT_coefs] [Mean_Age_Cross] [outputFolder_path]", "inputs": [{"command-line-flag": "--generate_cross_spectra", "default-value": false, "description": "Case False (0), the raw_data_path folder will contain the data_gatherer output. Case True (1) is required to calculate the cross spectra.", "value-key": "[generate_cross_spectra]", "type": "Flag", "list": false, "optional": true, "id": "generate_cross_spectra", "name": "Generate Cross Spectra"}, {"command-line-flag": "--raw_data_path", "description": "The content of this raw_data_path depends of generate_cross_spectra parameters: \n  1- If the generate_cross_spectra is False (0), this folder must be contain the data_gatherer output, with the cross spectra generated. (See more: https://github.com/CCC-members/BC-V_group_stat/blob/master/data_gatherer.m) \n 2- If the generate_cross_spectra is True (1), the raw_data_path can contain the following formats: BIDS, EDF, BDF, EEGLAB SET, Neuronic PLG, and a specified ASCII format (See more: https://github.com/tperezdevelopment/HarMNqEEG#data-gatherer).", "value-key": "[raw_data_path]", "type": "File", "list": false, "optional": false, "id": "raw_data_path", "name": "Folder path of the raw data"}, {"description": "The name of the output", "command-line-flag": "--outputFolder_path", "id": "output", "name": "output", "optional": true, "type": "String", "value-key": "[outputFolder_path]", "default-value": "HarMNqEEG_Outputs"}, {"command-line-flag": "--subjects_metadata", "description": "In case generate_cross_spectra is True this must be a *.csv, *.tsv or *.mat file format. This file must contain a list of subjects (See more: https://github.com/tperezdevelopment/HarMNqEEG#metadata).", "value-key": "[subjects_metadata]", "type": "File", "list": false, "optional": true, "id": "subjects_metadata", "name": "Subjects metadata"}, {"command-line-flag": "--log", "description": "Type of gaussianize method to apply. log-spectrum", "default-value": true, "value-key": "[log]", "type": "Flag", "list": false, "optional": true, "id": "log", "name": "Log Spectrum"}, {"command-line-flag": "--riemlogm", "description": "Type of gaussianize method to apply. Cross-spectrum in Tangent Space.", "default-value": true, "value-key": "[riemlogm]", "type": "Flag", "list": false, "optional": true, "id": "riemlogm", "name": "Cross-spectrum with Riemannian Vectorization."}, {"command-line-flag": "--batch_correction", "description": "List of the batch correction. You must select one of the following studies for calculating batch harmonized z-scores. The batch_correction you can put the number of the batch list or the batch correction name. The name of existed batch reference is the union between: EEG_Device+Country+Study_Year.", "value-key": "[batch_correction]", "type": "String", "value-choices": ["ANT_Neuro-Malaysia", "BrainAmp_DC-Chengdu_2014", "BrainAmp_MR_plus_64C-Chongqing", "BrainAmp_MR_plus-Germany_2013", "DEDAAS-Barbados_1978", "DEDAAS-NewYork_1970s", "EGI-256_HCGSN_Zurich_2017-Swiss", "Medicid-3M-Cuba_1990", "Medicid-4-Cuba_2003", "Medicid_128Ch-CHBMP", "NihonKohden-Bern_1980_Swiss", "actiCHamp_Russia_2013", "Neuroscan_synamps_2-Colombia", "nvx136-Russia_2013"], "optional": true, "id": "batch_correction", "name": "List of the batch correction."}, {"command-line-flag": "--FFT_coefs", "description": "Complex matrix of FFT coefficients of the EEG data (stored for possible needed further processing for calculating the cross-spectral matrix, like regularization algorithms in case of ill-conditioning).", "default-value": false, "value-key": "[FFT_coefs]", "type": "Flag", "list": false, "optional": true, "id": "FFT_coefs", "name": "Complex matrix of FFT coefficients of nd x nfreqs x epoch length."}, {"command-line-flag": "--Mean_Age_Cross", "description": "This is obtained by evaluating the Mean of the normative regression for the Raw Cross-Spectra in Tangent Space, at the subject\u2019s age.", "default-value": false, "value-key": "[Mean_Age_Cross]", "type": "Flag", "list": false, "optional": true, "id": "Mean_Age_Cross", "name": "Age evaluated Norms Mean of Cross-Spectra in Tangent Space."}], "containerimage": {"index": "docker://", "image": "tperezdevelopment90/harmnqeeg:1.0.0", "type": "singularity"}, "groups": [{"description": "Type of gaussianize method to apply. Options:", "one-is-required": true, "members": ["log", "riemlogm"], "id": "typeLog", "name": "typeLog"}, {"description": "List of matrix optional that the user can select. Options:", "one-is-required": false, "members": ["FFT_coefs", "Mean_Age_Cross"], "id": "optional_matrix", "name": "optional_matrix"}], "outputfiles": [{"description": "Path of output folder.", "id": "output_folder", "path-template": "[outputFolder_path]", "name": "Output folder.", "optional": false}], "suggestedresources": {"walltime-estimate": 5000}, "tooldoi": "https://doi.org/10.5281/zenodo.7017243", "url": "https://github.com/tperezdevelopment/HarMNqEEG", "ark_id": "https://n2t.net/ark:/70798/p72xp1cgg4qx10smrw", "platforms": [{"img": "/static/img/run_on_cbrain_green.png", "uri": "/cbrainredirect?cbrainurl=https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id%3D428"}]}, {"id": "zenodo.6859678", "title": "fNIRS Apps: Sourcedata to BIDS", "description": "Create fNIRS BIDS datasets from source data", "publicationdate": "2022-07-19", "deprecated": false, "downloads": 33, "author": "Robert Luke", "version": "v0.4.5", "doi": "10.5281/zenodo.6859678", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroimaging", "fnirs", "bids"]}, "name": "fNIRS Apps: Sourcedata to BIDS", "toolversion": "v0.4.5", "commandline": "/run.py [InputDataset] [SubjectLabel] [SessionLabel] [TaskLabel] [Events] [Duration] [OptodeFrame]", "containerimage": {"image": "ghcr.io/rob-luke/fnirs-apps-sourcedata2bids/app:v0.4.5", "index": "ghcr.io", "type": "docker", "entrypoint": true}, "inputs": [{"command-line-flag": "--input-datasets", "id": "input_datasets", "description": "The directory with the input dataset formatted according to the BIDS standard.", "name": "input-datasets", "optional": true, "type": "File", "value-key": "[InputDataset]"}, {"command-line-flag": "--subject-label", "description": "The label(s) of the subjects(s) that should be analyzed. The label corresponds to sub-<subject_label> from the BIDS spec (so it does not include \"sub-\"). If this parameter is not provided all subjects should be analyzed. Multiple participants can be specified with a space separated list.", "id": "subject_label", "name": "subject-label", "optional": true, "type": "String", "list": true, "value-key": "[SubjectLabel]"}, {"command-line-flag": "--session-label", "description": "The label(s) of the session(s) that should be analyzed. The label corresponds to ses-<session_label> from the BIDS spec (so it does not include \"ses-\"). If this parameter is not provided all sessions should be analyzed. Multiple sessions can be specified with a space separated list.", "id": "session_label", "name": "session-label", "optional": true, "type": "String", "list": true, "value-key": "[SessionLabel]"}, {"command-line-flag": "--task-label", "description": "The label(s) of the tasks(s) that should be analyzed. The label corresponds to task-<subject_label> from the BIDS spec. If this parameter is not provided all tasks should be analyzed. Multiple tasks can be specified with a space separated list.", "id": "task_label", "name": "task-label", "optional": true, "type": "String", "list": false, "value-key": "[TaskLabel]"}, {"command-line-flag": "--events", "id": "events", "name": "events", "optional": true, "type": "String", "value-key": "[Events]"}, {"command-line-flag": "--duration", "id": "duration", "name": "duration", "optional": true, "type": "Number", "value-key": "[Duration]"}, {"command-line-flag": "--optode-frame", "id": "optode_frame", "name": "optode_frame", "optional": true, "type": "String", "value-key": "[OptodeFrame]"}], "outputfiles": [{"id": "output_directory", "name": "BIDS directory", "optional": false, "path-template": "[InputDataset]"}], "suggestedresources": {"cpu-cores": 1, "ram": 1, "walltime-estimate": 60}, "errorcodes": [{"code": 1, "description": "Crashed"}], "custom": {"BIDSAppSpecVersion": "Draft"}, "ark_id": "https://n2t.net/ark:/70798/p7zd1jd4f09t7080r6", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.6518153", "title": "PhysIO_Tapas", "description": "Tapas Physio: Physiological noise correction for fMRI", "publicationdate": "2022-05-04", "deprecated": false, "downloads": 30, "author": "Lars Kasper, Zurich University and ETH Zurich", "version": "8.0", "doi": "10.5281/zenodo.6518153", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["neuroinformatics", "fMRI", "neuroimaging"]}, "toolversion": "8.0", "name": "PhysIO_Tapas", "descriptorurl": "https://github.com/dariusvalevicius/PhysIO_CBRAIN/blob/master/cbrain_task_descriptors/tapasphysio.json", "commandline": "mkdir -p [OUTDIR]; /usr/bin/mlrtapp/tapasphysio [use_case] [FMRI_IN] [OUTDIR] [correct] [log_files.align_scan] [log_files.cardiac] [log_files.cardiac_respiration] [log_files.relative_start_acquisition] [log_files.respiration] [log_files.scan_timing] [log_files.vendor] [log_files.sampling_interval] [model.censor_unreliable_recording_intervals] [model.hrv.delays] [model.hrv.include] [model.movement.censoring_method] [model.movement.censoring_threshold] [model.movement.file_realignment_parameters] [model.movement.include] [model.movement.order] [model.noise_rois.force_coregister] [model.noise_rois.include] [model.noise_rois.n_components] [model.noise_rois.n_voxel_crop] [model.noise_rois.thresholds] [model.noise_rois.fmri_files] [model.noise_rois.roi_files] [model.orthogonalise] [model.other.include] [model.other.input_multiple_regressors] [model.output_multiple_regressors] [model.output_physio] [model.retroicor.include] [model.retroicor.order.c] [model.retroicor.order.cr] [model.retroicor.order.r] [model.rvt.delays] [model.rvt.include] [preproc.cardiac.filter.passband] [preproc.cardiac.filter.type] [preproc.cardiac.initial_cpulse_select.file] [preproc.cardiac.initial_cpulse_select.max_heart_rate_bpm] [preproc.cardiac.initial_cpulse_select.method] [preproc.cardiac.initial_cpulse_select.min] [preproc.cardiac.modality] [preproc.cardiac.posthoc_cpulse_select.lower_thresh] [preproc.cardiac.posthoc_cpulse_select.method] [preproc.cardiac.posthoc_cpulse_select.file] [preproc.cardiac.posthoc_cpulse_select.percentile] [preproc.cardiac.posthoc_cpulse_select.upper_thresh] [preproc.cardiac.filter.include] [preproc.cardiac.filter.stopband] [scan_timing.sqpar.Ndummies] [scan_timing.sqpar.Nscans] [scan_timing.sqpar.Nslices] [scan_timing.sqpar.onset_slice] [scan_timing.sqpar.TR] [scan_timing.sqpar.NslicesPerBeat] [scan_timing.sqpar.time_slice_to_slice] [scan_timing.sqpar.Nprep] [scan_timing.sync.grad_direction] [scan_timing.sync.method] [scan_timing.sync.slice] [scan_timing.sync.zero] [scan_timing.sync.vol] [scan_timing.sync.vol_spacing] [verbose.fig_output_file] [verbose.level]", "containerimage": {"image": "dvalev/tapasphysio:version1.1.2", "index": "docker://", "type": "singularity"}, "inputs": [{"description": "Options for input formats.\nbids_subject_folder: Input the top level folder for a single subject. Must follow BIDS conventions. All contained fMRI runs will be processed.\nsingle_run_folder: Folder containing one run of data.\nmanual_input: Loose files as input. Must specify fMRI file and physlog files.\nWARNING: BIDS folder and single run folder options are currently experimental and may fail, especially with vendors other than BIDS and Philips. Only vendors which produce a single logfile for both resp+cardiac are supported at the moment.", "value-key": "[use_case]", "optional": false, "list": false, "value-choices": ["bids_directory", "manual_input"], "value-disables": {"bids_directory": ["log_files__cardiac", "log_files__respiration", "log_files__cardiac_respiration"], "manual_input": []}, "type": "String", "id": "use_case", "name": "Use Case"}, {"description": "Main input fMRI file or file collection.\nFor Manual Input, select fMRI file.\nFor BIDS or single run folder, select file collection.", "value-key": "[FMRI_IN]", "optional": false, "list": false, "type": "File", "id": "fmri_in", "name": "fMRI Input"}, {"description": "This will be added to the beginning of the output folder name.\nOutput will be of the form [output prefix]_[fmri input]", "value-key": "[OUT]", "optional": false, "list": false, "type": "String", "id": "out", "name": "Output folder prefix"}, {"description": "Produce corrected copies of fMRI images.", "default-value": "no", "value-key": "[correct]", "optional": false, "list": false, "value-choices": ["no", "yes"], "type": "String", "id": "correct", "name": "Correct noise"}, {"id": "log_files__vendor", "name": "Logfile Vendor", "value-key": "[log_files.vendor]", "default-value": "Philips", "type": "String", "description": "Vendor name depending on your MRI scanner/Physiological recording system.", "value-choices": ["BIDS", "Biopac_Txt", "Biopac_Mat", "BrainProducts", "Custom", "GE", "Philips", "Siemens", "Siemens_Tics", "Siemens_HCP"], "optional": false, "command-line-flag": "log_files.vendor"}, {"id": "log_files__cardiac", "name": "Cardiac Logfile", "value-key": "[log_files.cardiac]", "type": "File", "description": "Logfile with cardiac, i.e. ECG/PPU (pulse oximetry) data.\nSelect 0 files if only respiratory data is available.\nFor Philips and BIDS, same as respiratory logfile.", "optional": true, "command-line-flag": "log_files.cardiac"}, {"id": "log_files__respiration", "name": "Respiration Logfile", "value-key": "[log_files.respiration]", "type": "File", "description": "Logfile with respiratory, i.e. breathing belt amplitude data.", "optional": true, "command-line-flag": "log_files.respiration"}, {"id": "log_files__cardiac_respiration", "name": "Cardiac and Respiratory Logfile", "value-key": "[log_files.cardiac_respiration]", "type": "File", "description": "Logfile with both cardiac and respiratory data. For use with vendors where one file is given for both modalities (E.G. Philips, BIDS).", "optional": true, "command-line-flag": "log_files.cardiac_respiration"}, {"id": "log_files__relative_start_acquisition", "name": "Relative Start Acquisition", "value-key": "[log_files.relative_start_acquisition]", "default-value": 0, "type": "Number", "description": "Time (in seconds) when the 1st scan (or, if existing, dummy) started, relative to the start of the logfile recording:\n[] (empty) to read from explicit acquisition timing info\n0 if simultaneous start\n10, if 1st scan starts 10 seconds AFTER physiological recording\n-20, if first scan started 20 seconds BEFORE phys recording", "optional": true, "command-line-flag": "log_files.relative_start_acquisition"}, {"id": "log_files__align_scan", "name": "Align Scan", "value-key": "[log_files.align_scan]", "default-value": "last", "type": "String", "description": "Determines which scan shall be aligned to which part of the logfile.\nTypically, aligning the last scan to the end of the logfile is beneficial, since the start of the logfile and scans might be shifted due to pre-scans.", "value-choices": ["last", "first"], "optional": true, "command-line-flag": "log_files.align_scan"}, {"id": "log_files__scan_timing", "name": "Scan Timing", "value-key": "[log_files.scan_timing]", "type": "String", "description": "Additional file for relative timing information between logfiles and MRI scans.", "optional": true, "command-line-flag": "log_files.scan_timing"}, {"id": "log_files__sampling_interval", "name": "Sampling Interval", "value-key": "[log_files.sampling_interval]", "type": "String", "description": "Sampling interval of phys log files (in seconds).", "optional": true, "command-line-flag": "log_files.sampling_interval"}, {"id": "scan_timing__sqpar__Nslices", "name": "Number of Slices", "value-key": "[scan_timing.sqpar.Nslices]", "type": "Number", "description": "Number of slices in one volume.", "integer": true, "optional": true, "command-line-flag": "scan_timing.sqpar.Nslices"}, {"id": "scan_timing__sqpar__NslicesPerBeat", "name": "Number of Slices Per Beat", "value-key": "[scan_timing.sqpar.NslicesPerBeat]", "type": "Number", "description": "Only for triggered (gated) sequences:\nNumber of slices acquired per heartbeat", "integer": true, "optional": true, "command-line-flag": "scan_timing.sqpar.NslicesPerBeat"}, {"id": "scan_timing__sqpar__TR", "name": "TR", "value-key": "[scan_timing.sqpar.TR]", "type": "Number", "description": "Repetition time (in seconds) between consecutive image volumes.", "optional": true, "command-line-flag": "scan_timing.sqpar.TR"}, {"id": "scan_timing__sqpar__Ndummies", "name": "Number of Dummies", "value-key": "[scan_timing.sqpar.Ndummies]", "type": "Number", "description": "Number of dummies that were acquired (but will not show up in design matrix).", "integer": true, "optional": true, "command-line-flag": "scan_timing.sqpar.Ndummies"}, {"id": "scan_timing__sqpar__Nscans", "name": "Number of scans", "value-key": "[scan_timing.sqpar.Nscans]", "type": "Number", "description": "Number of scans (volumes) in design matrix.", "optional": true, "command-line-flag": "scan_timing.sqpar.Nscans"}, {"id": "scan_timing__sqpar__onset_slice", "name": "Onset Slice", "value-key": "[scan_timing.sqpar.onset_slice]", "type": "Number", "description": "Slice to which regressors are temporally aligned.\nTypically the slice where your most important activation is expected.", "integer": true, "optional": true, "command-line-flag": "scan_timing.sqpar.onset_slice"}, {"id": "scan_timing__sqpar__time_slice_to_slice", "name": "Time Slice-to-Slice", "value-key": "[scan_timing.sqpar.time_slice_to_slice]", "type": "Number", "description": "Duration between acquisition of two different slices.\nIf empty, set to default value (TR/Nslices).", "optional": true, "command-line-flag": "scan_timing.sqpar.time_slice_to_slice"}, {"id": "scan_timing__sqpar__Nprep", "name": "Number of Preparation Pulses", "value-key": "[scan_timing.sqpar.Nprep]", "type": "Number", "description": "Count of preparation pulses BEFORE 1st dummy scan.\nOnly important if Align Scan = 'first', since then preparation pulses and dummy triggers are counted and discarded as first scan onset.", "optional": true, "command-line-flag": "scan_timing.sqpar.Nprep"}, {"id": "scan_timing__sync__method", "name": "Sync Method", "value-key": "[scan_timing.sync.method]", "default-value": "nominal", "type": "String", "description": "Determines scan timing from nominal scan parameters or logged gradient time courses.", "value-choices": ["nominal", "gradient_log", "gradient_log_auto", "scan_timing_log"], "value-disables": {"nominal": ["scan_timing__sync__grad_direction", "scan_timing__sync__zero", "scan_timing__sync__slice", "scan_timing__sync__vol", "scan_timing__sync__vol_spacing"], "gradient_log": [], "gradient_log_auto": ["scan_timing__sync__grad_direction", "scan_timing__sync__zero", "scan_timing__sync__slice", "scan_timing__sync__vol", "scan_timing__sync__vol_spacing"], "scan_timing_log": ["scan_timing__sync__grad_direction", "scan_timing__sync__zero", "scan_timing__sync__slice", "scan_timing__sync__vol", "scan_timing__sync__vol_spacing"]}, "optional": true, "command-line-flag": "scan_timing.sync.method"}, {"id": "scan_timing__sync__grad_direction", "name": "Gradient Direction", "value-key": "[scan_timing.sync.grad_direction]", "type": "String", "description": "Must choose x,y, or z.", "value-choices": ["x", "y", "z"], "optional": true, "command-line-flag": "scan_timing.sync.grad_direction"}, {"id": "scan_timing__sync__zero", "name": "Gradient Zero", "value-key": "[scan_timing.sync.zero]", "type": "Number", "description": "Gradient amplitude threshold below which values will be set to zero.", "optional": true, "command-line-flag": "scan_timing.sync.zero"}, {"id": "scan_timing__sync__slice", "name": "Gradient Slice", "value-key": "[scan_timing.sync.slice]", "type": "Number", "description": "Gradient amplitude threshold for start of new slice.", "optional": true, "command-line-flag": "scan_timing.sync.slice"}, {"id": "scan_timing__sync__vol", "name": "Gradient Volume", "value-key": "[scan_timing.sync.vol]", "type": "Number", "description": "Gradient amplitude threshold for start of new volume.\nOptional parameter - can be used if volume start indicated by higher gradient amplitude.\nMutually exclusive with use of vol_spacing parameter.", "optional": true, "command-line-flag": "scan_timing.sync.slice"}, {"id": "scan_timing__sync__vol_spacing", "name": "Gradient Volume Spacing", "value-key": "[scan_timing.sync.vol_spacing]", "type": "Number", "description": "Gradient amplitude threshold for start of new volume.\nOptional parameter - can be used if volume start indicated by higher gradient amplitude.\nMutually exclusive with use of vol_spacing parameter.", "optional": true, "command-line-flag": "scan_timing.sync.slice"}, {"id": "preproc__cardiac__modality", "name": "Cardiac Modality", "value-key": "[preproc.cardiac.modality]", "default-value": "ECG", "type": "String", "description": "Shall ECG or PPU data be read from logfiles?", "value-choices": ["ECG", "ECG_raw", "OXY", "PPU_WiFi"], "optional": true, "command-line-flag": "preproc.cardiac.modality"}, {"id": "preproc__cardiac__filter__include", "name": "Filter Raw Cardiac Time Series", "value-key": "[preproc.cardiac.filter.include]", "default-value": "no", "type": "String", "description": "Filter properties for bandpass-filtering of cardiac signal before peak detection, phase extraction, and other physiological traces.", "value-choices": ["no", "yes"], "value-disables": {"no": ["preproc__cardiac__filter__type", "preproc__cardiac__filter__passband", "preproc__cardiac__filter__stopband"], "yes": []}, "optional": true, "command-line-flag": "preproc.cardiac.filter.include"}, {"id": "preproc__cardiac__filter__type", "name": "Filter Type", "value-key": "[preproc.cardiac.filter.type]", "default-value": "butter", "type": "String", "description": "Which infinite impulse response filter shall be used?\n'Chebychev Type II (cheby2)': Chebychev Type II filter, use for steep transition from start to stop band\n'Butterworth (butter)': Butterworth filter, standard filter with maximally flat passband (Infinite impulse response), but stronger ripples in transition band", "value-choices": ["butter", "cheby2"], "optional": true, "command-line-flag": "preproc.cardiac.filter.type"}, {"id": "preproc__cardiac__filter__passband", "name": "Filter Passband", "value-key": "[preproc.cardiac.filter.passband]", "default-value": [0.3, 9], "type": "Number", "description": "[f_min, f_max] frequency interval in Hz of all frequency that should pass the passband filter.\nIf empty, no filtering is performed.]", "optional": true, "list": true, "list-separator": ",", "command-line-flag": "preproc.cardiac.filter.passband"}, {"id": "preproc__cardiac__filter__stopband", "name": "Filter Stopband", "value-key": "[preproc.cardiac.filter.stopband]", "type": "Number", "description": "[f_min, f_max] frequency interval in Hz of all frequencies, such that frequencies outside this band should definitely NOT pass the filter.\nNOTE: only relevant for 'cheby2' filter type.\nIf empty, and passband is empty, no fitlering is performed.\nIf empty, but passband exists, stopband interval is 10% increased passband interval.", "optional": true, "list": true, "list-separator": ",", "command-line-flag": "preproc.cardiac.filter.stopband"}, {"id": "preproc__cardiac__initial_cpulse_select__method", "name": "Cardiac Pulse Selection Method", "value-key": "[preproc.cardiac.initial_cpulse_select.method]", "default-value": "auto_matched", "type": "String", "description": "The initial cardiac pulse selection structure: Determines how the majority of cardiac pulses is detected in a first pass.", "value-choices": ["auto_matched", "load_from_logfile", "manual", "load"], "value-disables": {"auto_matched": [], "load_from_logfile": ["preproc__cardiac__initial_cpulse_select__min", "preproc__cardiac__initial_cpulse_select__file", "preproc__cardiac__initial_cpulse_select__max_heart_rate_bpm"], "manual": ["preproc__cardiac__initial_cpulse_select__max_heart_rate_bpm"], "load": ["preproc__cardiac__initial_cpulse_select__max_heart_rate_bpm"]}, "optional": true, "command-line-flag": "preproc.cardiac.initial_cpulse_select.method"}, {"id": "preproc__cardiac__initial_cpulse_select__min", "name": "Cardiac Pulse Selection Minimum", "value-key": "[preproc.cardiac.initial_cpulse_select.min]", "default-value": 0.4, "type": "Number", "description": "Minimum threshold for peak height in z-scored cardiac waveform to find pulse events.\nNOTE: For ECG, might need increase (e.g., 2.0), because of local maximum of T wave after QRS complex.", "optional": true, "command-line-flag": "preproc.cardiac.initial_cpulse_select.min"}, {"id": "preproc__cardiac__initial_cpulse_select__file", "name": "Cardiac Pulse Selection File", "value-key": "[preproc.cardiac.initial_cpulse_select.file]", "default-value": "initial_cpulse_kRpeakfile.mat", "type": "String", "description": "File containing reference ECG-peak (variable kRpeak),\nUsed for method 'manual' or 'load'.\nIf method == 'manual', this file is saved after picking the QRS-wave such that results are reproducible.", "optional": true, "command-line-flag": "preproc.cardiac.initial_cpulse_select.file"}, {"id": "preproc__cardiac__initial_cpulse_select__max_heart_rate_bpm", "name": "Maximum Heart Rate (BPM)", "value-key": "[preproc.cardiac.initial_cpulse_select.max_heart_rate_bpm]", "default-value": 90, "type": "Number", "description": "Maximum expected heart rate in beats per minute.\nThis only needs to be a rough guess and should be changed for specific populations.", "optional": true, "command-line-flag": "preproc.cardiac.initial_cpulse_select.max_heart_rate_bpm"}, {"id": "preproc__cardiac__posthoc_cpulse_select__method", "name": "Post-Hoc Selection of Cardiac Pulses", "value-key": "[preproc.cardiac.posthoc_cpulse_select.method]", "default-value": "off", "type": "String", "description": "The post-hoc cardiac pulse selection structure: if only few (<20) cardiac pulses are missing in a session due to bad signal quality, a manual selection after visual inspection is possible using the following parameters. The results are saved for reproducibility.", "value-choices": ["off", "manual", "load"], "value-disables": {"off": ["preproc__cardiac__posthoc_cpulse_select__file", "preproc__cardiac__posthoc_cpulse_select__percentile", "preproc__cardiac__posthoc_cpulse_select__upper_thresh", "preproc__cardiac__posthoc_cpulse_select__lower_thresh"], "manual": [], "load": ["preproc__cardiac__posthoc_cpulse_select__file"]}, "optional": true, "command-line-flag": "preproc.cardiac.posthoc_cpulse_select.method"}, {"id": "preproc__cardiac__posthoc_cpulse_select__file", "name": "Post-Hoc Selection File", "value-key": "[preproc.cardiac.posthoc_cpulse_select.file]", "type": "String", "description": "Filename where cardiac pulses are saved after manual picking.", "optional": true, "command-line-flag": "preproc.cardiac.posthoc_cpulse_select.file"}, {"id": "preproc__cardiac__posthoc_cpulse_select__percentile", "name": "Post-Hoc Selection Percentile", "value-key": "[preproc.cardiac.posthoc_cpulse_select.percentile]", "default-value": 80, "type": "Number", "description": "Percentile of beat-2-beat interval histogram that constitutes the average heart beat duration in the session.", "optional": true, "command-line-flag": "preproc.cardiac.posthoc_cpulse_select.percentile"}, {"id": "preproc__cardiac__posthoc_cpulse_select__upper_thresh", "name": "Post-Hoc Selection Upper Threshold", "value-key": "[preproc.cardiac.posthoc_cpulse_select.upper_thresh]", "default-value": 60, "type": "Number", "description": "Minimum exceedance (in %) from average heartbeat duration to be classified as missing heartbeat.", "optional": true, "command-line-flag": "preproc.cardiac.posthoc_cpulse_select.upper_thresh"}, {"id": "preproc__cardiac__posthoc_cpulse_select__lower_thresh", "name": "Post-Hoc Selection Lower Threshold", "value-key": "[preproc.cardiac.posthoc_cpulse_select.lower_thresh]", "default-value": 60, "type": "Number", "description": "Minimum reduction (in %) from average heartbeat duration to be classified an abundant heartbeat.", "optional": true, "command-line-flag": "preproc.cardiac.posthoc_cpulse_select.lower_thresh"}, {"id": "model__output_multiple_regressors", "name": "Output File for Multiple Regressors", "value-key": "[model.output_multiple_regressors]", "default-value": "multiple_regressors.txt", "type": "String", "description": "Output file for physiological regressors.\nChoose file name with extension:\n.txt for ASCII files with 1 regressor per column\n.mat for MATLAB variable file", "optional": true, "command-line-flag": "model.output_multiple_regressors"}, {"id": "model__output_physio", "name": "Output Physio Structure", "value-key": "[model.output_physio]", "default-value": "physio.mat", "type": "String", "description": "Output file for physio-structure with extracted physiological time series, detected peak and created regressors.\nChoose mat-file name; structure will be saved as variable physio in there.", "optional": true, "command-line-flag": "model.output_physio"}, {"id": "model__orthogonalise", "name": "Orthogonalise", "value-key": "[model.orthogonalise]", "default-value": "none", "type": "String", "description": "Orthogonalise physiological regressors with respect to each other.\nNOTE: This is only recommended for triggered/gated acquisition sequences.", "value-choices": ["none", "cardiac", "resp", "mult", "all", "RETROICOR", "HRV", "RVT", "movement", "noise_rois"], "optional": true, "command-line-flag": "model.orthogonalise"}, {"id": "model__censor_unreliable_recording_intervals", "name": "Censor Unreliable Recording Intervals", "value-key": "[model.censor_unreliable_recording_intervals]", "default-value": "no", "type": "String", "description": "If parts of the physiological recording intervals are unreliable (e.g., constant due to belt detachment) the corresponding parts of recording-dependent RETROICOR regressors are set to 0 in the final multiple regressors file.", "value-choices": ["yes", "no"], "optional": true, "command-line-flag": "model.censor_unreliable_recording_intervals"}, {"id": "model__retroicor__include", "name": "Include RETROICOR", "value-key": "[model.retroicor.include]", "default-value": "yes", "type": "String", "description": "Include RETROICOR Model, as described in Glover et al., MRM 2000.", "value-choices": ["yes", "no"], "value-disables": {"no": ["model__retroicor__order__c", "model__retroicor__order__r", "model__retroicor__order__cr"], "yes": []}, "optional": true, "command-line-flag": "model.retroicor.include"}, {"id": "model__retroicor__order__c", "name": "RETROICOR Cardiac Order", "value-key": "[model.retroicor.order.c]", "default-value": 3, "type": "Number", "description": "Order of Fourier expansion for cardiac phase.\nEquals 1/2 number of cardiac regressors, since sine and cosine terms are computed.", "integer": true, "optional": true, "command-line-flag": "model.retroicor.order.c"}, {"id": "model__retroicor__order__r", "name": "RETROICOR Respiratory Order", "value-key": "[model.retroicor.order.r]", "default-value": 4, "type": "Number", "description": "Order of Fourier expansion for respiratory phase.\nEquals 1/2 number of respiratory regressors, since sine and cosine terms are computed.", "integer": true, "optional": true, "command-line-flag": "model.retroicor.order.r"}, {"id": "model__retroicor__order__cr", "name": "RETROICOR Cardiac X Respiratory Order", "value-key": "[model.retroicor.order.cr]", "default-value": 1, "type": "Number", "description": "Order of Fourier expansion for interaction of cardiac and respiratory phase.\nEquals 1/4 number of interaction regressors, since since and cosine terms are computed and multiplied.", "integer": true, "optional": true, "command-line-flag": "model.retroicor.order.cr"}, {"id": "model__rvt__include", "name": "Include Respiratory Volume per Time (RVT)", "value-key": "[model.rvt.include]", "default-value": "no", "type": "String", "description": "Respiratory Volume per Time (RVT) Model, as described in Birn et al. NeuroImage 40, 644-654.", "value-choices": ["yes", "no"], "value-disables": {"no": ["model__rvt__delays"], "yes": []}, "optional": true, "command-line-flag": "model.rvt.include"}, {"id": "model__rvt__delays", "name": "RVT Delays", "value-key": "[model.rvt.delays]", "default-value": 0, "type": "Number", "description": "Delays (in seconds) by which respiratory response function is shifted with respect to RVT regressor before convolution.", "optional": true, "command-line-flag": "model.rvt.delays"}, {"id": "model__hrv__include", "name": "Include Heart Rate Variability (HRV)", "value-key": "[model.hrv.include]", "default-value": "no", "type": "String", "description": "Heart Rate Variability (HRV) Model, as described in Chang et al., NeuroImage 44, 857-869.", "value-choices": ["yes", "no"], "value-disables": {"no": ["model__hrv__delays"], "yes": []}, "optional": true, "command-line-flag": "model.hrv.include"}, {"id": "model__hrv__delays", "name": "HRV Delays", "value-key": "[model.hrv.delays]", "default-value": 0, "type": "Number", "description": "Delays (in seconds) by which respiratory response function is shifted with respect to HRV regressor before convolution.", "optional": true, "command-line-flag": "model.hrv.delays"}, {"id": "model__noise_rois__include", "name": "Include Noise ROIs", "value-key": "[model.noise_rois.include]", "default-value": "no", "type": "String", "description": "Noise ROIs model (Principal components of anatomical regions), similar to aCompCor, Hehzadi et al. 2007.", "value-choices": ["yes", "no"], "value-disables": {"no": ["model__noise_rois__fmri_files", "model__noise_rois__roi_files", "model__noise_rois__force_coregister", "model__noise_rois__thresholds", "model__noise_rois__n_voxel_crop", "model__noise_rois__n_components"], "yes": []}, "optional": true, "command-line-flag": "model.noise_rois.include"}, {"id": "model__noise_rois__fmri_files", "name": "fMRI Time Series File(s)", "value-key": "[model.noise_rois.fmri_files]", "type": "String", "description": "Preprocessed fmri nifti/analyze files, from which time series shall be extracted.", "optional": true, "command-line-flag": "model.noise_rois.fmri_files"}, {"id": "model__noise_rois__roi_files", "name": "Noise ROI Image File(s)", "value-key": "[model.noise_rois.roi_files]", "type": "String", "description": "Masks/tissues probability maps characterizing where noise resides.\nThese volumes must be in the same space as the functional colume where the time series will be extracted.", "optional": true, "command-line-flag": "model.noise_rois.roi_files"}, {"id": "model__noise_rois__force_coregister", "name": "Force Coregister: Estimate & Reslice of the noise ROIs", "value-key": "[model.noise_rois.force_coregister]", "default-value": "yes", "type": "String", "description": "Noise ROIs volumes must have the same geometry as the functional time series.\nUt neabs sane affine transformation (space) and same matrix (voxel size).", "value-choices": ["yes", "no"], "optional": true, "command-line-flag": "model.noise_rois.force_coregister"}, {"id": "model__noise_rois__thresholds", "name": "ROI thresholds", "value-key": "[model.noise_rois.thresholds]", "default-value": 0.9, "type": "Number", "description": "Single threshold or vector [1, nRois] of thresholds to be applied to mask files to decide which voxels to include (e.g. a probability like 0.99, if roi files are tissue probability maps)", "optional": true, "command-line-flag": "model.noise_rois.thresholds"}, {"id": "model__noise_rois__n_voxel_crop", "name": "Number of ROI pixels to be cropped", "value-key": "[model.noise_rois.n_voxel_crop]", "default-value": 0, "type": "Number", "description": "Single number or vector [1, nRois] of number of voxels to crop per ROI.", "integer": true, "optional": true, "command-line-flag": "model.noise_rois.n_voxel_crop"}, {"id": "model__noise_rois__n_components", "name": "Number of principal components", "value-key": "[model.noise_rois.n_components]", "default-value": 1, "type": "Number", "description": "Single number or vector [1, nRois] of numbers.\nInteger >- 1: Number of principal components to be extracted from all voxel time series within each ROI\nFloat in [0,1[: Choose as many components as needed to explain this relative shae of the variance.", "integer": true, "optional": true, "command-line-flag": "model.noise_rois.n_components"}, {"id": "model__movement__include", "name": "Include Movement Model", "value-key": "[model.movement.include]", "default-value": "no", "type": "String", "description": "Motion Assessment and Regression Models\nMotion 6/12/24 regressors from realignment as described in Friston et al., 1996\nMotion Censoring ('spike' regressors for motion-corrupted volumes)\nMotion scrubbing (linear interpolation of censored volumes by nearest neighbours)", "value-choices": ["yes", "no"], "value-disables": {"no": ["model__movement__file_realignment_parameters", "model__movement__order", "model__movement__censoring_method", "model__movement__censoring_threshold"], "yes": []}, "optional": true, "command-line-flag": "model.movement.include"}, {"id": "model__movement__file_realignment_parameters", "name": "Movement Realignment Parameter File", "value-key": "[model.movement.file_realignment_parameters]", "type": "String", "optional": true, "command-line-flag": "model.movement.file_realignment_parameters"}, {"id": "model__movement__order", "name": "Movement Order", "value-key": "[model.movement.order]", "default-value": 6, "type": "Number", "description": "Order of movement regressors 6/12/24, including derivatives and squared parameters/derivatives.", "integer": true, "value-choices": [6, 12, 24], "optional": true, "command-line-flag": "model.movement.order"}, {"id": "model__movement__censoring_method", "name": "Movement Censoring Method for Thresholding", "value-key": "[model.movement.censoring_method]", "default-value": "FD", "type": "String", "description": "Censoring method used for thresholding", "value-choices": ["none", "MAXVAL", "FD", "DVARS"], "optional": true, "command-line-flag": "model.movement.censoring_method"}, {"id": "model__movement__censoring_threshold", "name": "Movement Censoring Outlier Threshold", "value-key": "[model.movement.censoring_threshold]", "default-value": 0.5, "type": "Number", "description": "Threshold, above which a stick ('spike') regressors is created for corresponding outlier volume exceeding threshold.", "optional": true, "command-line-flag": "model.movement.censoring_threshold"}, {"id": "model__other__include", "name": "Include Other Multiple Regressors", "value-key": "[model.other.include]", "default-value": "no", "type": "String", "description": "Other multiple regressor file(s).", "value-choices": ["yes", "no"], "value-disables": {"no": ["model__other__input_multiple_regressors"], "yes": []}, "optional": true, "command-line-flag": "model.other.include"}, {"id": "model__other__input_multiple_regressors", "name": "Input Multiple Regressors Files", "value-key": "[model.other.input_multiple_regressors]", "type": "String", "optional": true, "command-line-flag": "model.other.input_multiple_regressors"}, {"id": "verbose__level", "name": "Verbose Level", "value-key": "[verbose.level]", "default-value": 2, "type": "Number", "description": "Determines how many figures shall be generated to follow the workflow of the toolbox and whether the graphical output shall be saved.\n0 = No graphical output\n1 = Main plots\n2 = Debugging plots\n3 = All plots", "integer": true, "optional": true, "command-line-flag": "verbose.level"}, {"id": "verbose__fig_output_file", "name": "Figure Output File Name", "value-key": "[verbose.fig_output_file]", "default-value": "PhysIO_output.jpg", "type": "String", "description": "File name where figures are saved to.\nSupported figure formats (via filename suffix): jpg, png, fig, ps", "optional": true, "command-line-flag": "verbose.fig_output_file"}], "groups": [{"description": "Specify log files where peripheral data was stored, and their properties.", "id": "log_files_group", "members": ["log_files__vendor", "log_files__cardiac", "log_files__respiration", "log_files__cardiac_respiration", "log_files__scan_timing", "log_files__sampling_interval", "log_files__relative_start_acquisition", "log_files__align_scan"], "name": "Log File Parameters"}, {"description": "Parameters for scan timing and synchronization.", "id": "scan_timing_group", "members": ["scan_timing__sqpar__Nslices", "scan_timing__sqpar__NslicesPerBeat", "scan_timing__sqpar__TR", "scan_timing__sqpar__Ndummies", "scan_timing__sqpar__Nscans", "scan_timing__sqpar__onset_slice", "scan_timing__sqpar__time_slice_to_slice", "scan_timing__sqpar__Nprep", "scan_timing__sync__method", "scan_timing__sync__grad_direction", "scan_timing__sync__zero", "scan_timing__sync__vol", "scan_timing__sync__vol_spacing", "scan_timing__sync__slice"], "name": "Scan Timing Parameters"}, {"description": "Thresholding parameters for de-noising and timing", "id": "preproc_group", "members": ["preproc__cardiac__modality", "preproc__cardiac__filter__include", "preproc__cardiac__filter__type", "preproc__cardiac__filter__passband", "preproc__cardiac__filter__stopband", "preproc__cardiac__initial_cpulse_select__method", "preproc__cardiac__initial_cpulse_select__min", "preproc__cardiac__initial_cpulse_select__file", "preproc__cardiac__initial_cpulse_select__max_heart_rate_bpm", "preproc__cardiac__posthoc_cpulse_select__method", "preproc__cardiac__posthoc_cpulse_select__file", "preproc__cardiac__posthoc_cpulse_select__percentile", "preproc__cardiac__posthoc_cpulse_select__upper_thresh", "preproc__cardiac__posthoc_cpulse_select__lower_thresh"], "name": "Preprocessing Paramaters"}, {"description": "Physiological model to be estimated and included in GLM as multiple_regressors.txt.", "id": "model_group", "members": ["model__output_multiple_regressors", "model__output_physio", "model__orthogonalise", "model__censor_unreliable_recording_intervals", "model__retroicor__include", "model__retroicor__order__c", "model__retroicor__order__r", "model__retroicor__order__cr", "model__rvt__include", "model__rvt__delays", "model__hrv__include", "model__hrv__delays", "model__noise_rois__include", "model__noise_rois__fmri_files", "model__noise_rois__roi_files", "model__noise_rois__force_coregister", "model__noise_rois__thresholds", "model__noise_rois__n_voxel_crop", "model__noise_rois__n_components", "model__movement__include", "model__movement__file_realignment_parameters", "model__movement__order", "model__movement__censoring_method", "model__movement__censoring_threshold", "model__other__include", "model__other__input_multiple_regressors"], "name": "Model Parameters"}, {"description": "Figure generation options", "id": "verbose_group", "members": ["verbose__level", "verbose__fig_output_file"], "name": "Verbose Parameters"}], "outputfiles": [{"description": "A folder containing the output files and a copy of configs.", "list": false, "id": "output", "value-key": "[OUTDIR]", "optional": true, "path-template": "[OUT]_[FMRI_IN]", "path-template-stripped-extensions": [".nii.gz", ".nii"], "name": "Output folder"}], "suggestedresources": {"walltime-estimate": 3660}, "custom": {"cbrain:author": "Darius Valevicius <darius.valevicius@mail.mcgill.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7jr133x44q4w2xzdp", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7343403", "title": "FreeSurfer-Recon-all-qcache", "description": "resample longitudinal data onto the average subject (called fsaverage) & smooth it at a range of FWHM: (https://surfer.nmr.mgh.harvard.edu/fswiki/qcache).", "publicationdate": "2022-11-21", "deprecated": false, "downloads": 30, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.1.1", "doi": "10.5281/zenodo.7343225", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer-Recon-all-qcache", "containerimage": {"index": "docker://", "image": "freesurfer/freesurfer:7.1.1", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; recon-all -long [TP] [BASE] -qcache", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "timepoint", "id": "tp", "optional": false, "value-key": "[TP]", "description": "input timepoint", "type": "String"}, {"name": "base template", "id": "base", "optional": false, "value-key": "[BASE]", "description": "subject template", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7h3g2cdf7fn709cp6", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.6515427", "title": "oxford_asl", "description": "oxford_asl is part of BASIL (https://asl-docs.readthedocs.io/en/latest/oxford_asl_userguide.html)", "publicationdate": "2022-05-03", "deprecated": false, "downloads": 30, "author": "Oxford Centre for Functional MRI of the Brain (FMRIB)", "version": "6.0.4", "doi": "10.5281/zenodo.6515427", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["neuroinformatics", "mri"]}, "toolversion": "6.0.4", "descriptorurl": "https://github.com/aces/cbrain-plugins-neuro/blob/master/cbrain_task_descriptors/oxford_asl.json", "custom": {"cbrain:author": "Natacha Beck", "cbrain:readonly-input-files": true}, "inputs": [{"command-line-flag": "-i", "value-key": "[INPUT_FILE]", "optional": false, "id": "asl_data", "type": "File", "description": "ASL data input", "list": false, "name": "Asl data"}, {"command-line-flag": "-m", "value-key": "[MASK]", "optional": true, "id": "mask", "type": "File", "description": "Mask (in native space of ASL data) - {default: automatically generated}", "list": false, "name": "Mask"}, {"command-line-flag": "--spatial", "type": "String", "optional": true, "id": "spatial", "value-choices": ["on", "off"], "value-key": "[SPATIAL]", "description": "Perform ASL analysis with automatic spatial smoothing of CBF (could be set to 'off')", "command-line-flag-separator": "=", "list": false, "name": "Spatial smoothing"}, {"command-line-flag": "--wp", "value-key": "[WP]", "optional": true, "id": "white_perform", "type": "Flag", "description": "Analysis that conforms to the 'white paper' (Alsop et al. 2014)", "list": false, "name": "White paper mode"}, {"command-line-flag": "--mc", "value-key": "[MC]", "optional": true, "id": "motion_correction", "type": "Flag", "description": "Apply motion correction using mcflirt", "list": false, "name": "Motion correction"}, {"command-line-flag": "--iaf", "type": "String", "optional": true, "default-value": "diff", "id": "iaf", "value-choices": ["diff", "tc", "ct"], "value-key": "[IAF]", "description": "Input ASL format", "list": false, "name": "Input ASL format"}, {"command-line-flag": "--ibf", "value-key": "[IBF]", "optional": true, "id": "ibf", "value-choices": ["rpt", "tis"], "type": "String", "description": "Input block format (for multi-TI)", "list": false, "name": "Input block format"}, {"command-line-flag": "--tis", "value-key": "[TIS]", "optional": true, "id": "tis", "type": "String", "description": "comma separated list of inflow times in seconds, e.g. --tis 0.2,0.4,0.6", "command-line-flag-separator": "=", "list": false, "name": "Inversion time"}, {"command-line-flag": "--tiimg", "value-key": "[TIIMG]", "optional": true, "id": "tiimg", "type": "File", "description": "4D image containing voxelwise TI values", "list": false, "name": "4D image"}, {"command-line-flag": "--casl", "value-key": "[CASL]", "optional": true, "id": "casl", "type": "Flag", "description": "ASL acquisition is  pseudo cASL (pcASL) rather than pASL", "list": false, "name": "Casl"}, {"command-line-flag": "--artsupp", "value-key": "[ARTSUPP]", "optional": true, "id": "artsupp", "type": "Flag", "description": "Arterial suppression (vascular crushing) was used, same as artoff", "list": false, "name": "Arterial suppression"}, {"command-line-flag": "--fixbolus", "value-key": "[FIXBOLUS]", "optional": true, "id": "fixbolus", "type": "String", "description": "Turn off automatic estimation of bolus duration as it is fixed, e.g. by QUIPSSII or CASL", "list": false, "name": "Fix bolus duration"}, {"command-line-flag": "--bolus", "value-key": "[BOLUS]", "optional": true, "id": "bolus", "type": "String", "description": "Duration of the ASL labeling bolus in seconds - {default: 1}", "command-line-flag-separator": "=", "list": false, "name": "Bolus duration"}, {"command-line-flag": "--bat", "value-key": "[BAT]", "optional": true, "id": "bat", "type": "String", "description": "Bolus arrival time in seconds - {default: 0.7 (pASL); 1.3 (cASL)}", "command-line-flag-separator": "=", "list": false, "name": "Bolus arrival time"}, {"command-line-flag": "--t1", "type": "String", "optional": true, "default-value": "1.3", "id": "t1", "value-key": "[T1]", "description": "Tissue T1 value - {default: 1.3}", "command-line-flag-separator": "=", "list": false, "name": "Tissue T1 value"}, {"command-line-flag": "--t1b", "type": "String", "optional": true, "default-value": "1.65", "id": "t1b", "value-key": "[T1B]", "description": "Blood T1 value - {default: 1.65}", "command-line-flag-separator": "=", "list": false, "name": "Blood T1"}, {"command-line-flag": "--slicedt", "type": "String", "optional": true, "default-value": "0", "id": "slicedt", "value-key": "[SLICEDT]", "description": "Timing difference between slices in seconds - {default: 0}", "command-line-flag-separator": "=", "list": false, "name": "Timing difference"}, {"command-line-flag": "--sliceband", "value-key": "[SLICEBAND]", "optional": true, "id": "sliceband", "type": "String", "description": "Number of slices per band in a multi-band setup", "command-line-flag-separator": "=", "list": false, "name": "Number of slices"}, {"command-line-flag": "--rpts", "value-key": "[RPTS]", "optional": true, "id": "rpts", "type": "String", "description": " Number of repeated measurements for each TI/PLD in the TIs list, for use where the number of repeated measurements varies at each TI.", "command-line-flag-separator": "=", "list": false, "name": "Number of repeated measurements"}, {"value-key": "[FSLANAT]", "optional": true, "id": "fslanat", "type": "File", "description": "An existing fsl_anat directory from structural image", "list": false, "name": "fsl_anat directory"}, {"value-key": "[FSL_INFILE]", "optional": true, "id": "infile", "type": "File", "description": "Run Anat FSL with a single input image file, such as .nii.gz. The result will be used with Oxford ASL --fslanat option", "list": false, "name": "An image to run FSL Anat with before Oxford Asl"}, {"command-line-flag": "-s", "value-key": "[S]", "optional": true, "id": "s", "type": "File", "description": "Structural image (whole head)", "list": false, "name": "Structural image"}, {"command-line-flag": "--sbrain", "value-key": "[SBRAIN]", "optional": true, "id": "sbrain", "type": "File", "description": "Structural image (already BETed)", "list": false, "name": "Structural image"}, {"command-line-flag": "--fastsrc", "value-key": "[FASTSRC]", "optional": true, "id": "fastsrc", "type": "File", "description": "Images from a FAST segmenation - if not set FAST will be run on structural", "list": false, "name": "Images from FAST"}, {"command-line-flag": "--senscorr", "value-key": "[SENSCORR]", "optional": true, "id": "senscorr", "type": "Flag", "description": "use bias field (from segmentation) for sensitivity correction", "list": false, "name": "Bias field"}, {"command-line-flag": "--M0", "value-key": "[M0]", "optional": true, "id": "m0", "type": "String", "description": "(single) precomputed M0 value (e.g. from having run a separate calibration)", "list": false, "name": "M0 value"}, {"command-line-flag": "--alpha", "value-key": "[ALPHA]", "optional": true, "id": "alpha", "type": "String", "description": "Inversion efficiency - {default: 0.98 (pASL); 0.85 (cASL)}", "list": false, "name": "Inversion efficiency"}, {"command-line-flag": "-c", "value-key": "[C]", "optional": true, "id": "c", "type": "File", "description": "M0 calibration image (proton density or mean control image)", "list": false, "name": "M0 calibration"}, {"command-line-flag": "--tr", "value-key": "[TR]", "optional": true, "default-value": "3.2", "id": "tr", "type": "String", "description": "Repetition time of calibration in seconds - {default: 3.2 s}", "list": false, "name": "TR of calibration"}, {"command-line-flag": "--cmethod", "value-key": "[CMETHOD]", "optional": true, "id": "cmethod", "value-choices": ["single", "voxel"], "type": "String", "description": "Single - default if structural image is supplied M0 value will be calculated within automatically created CSF mask || voxel  - default if no structral image is supplied voxelwise M0 values derrived from calibration image", "list": false, "name": "Calibration method"}, {"command-line-flag": "--t2csf", "value-key": "[T2CSF]", "optional": true, "id": "t2csf", "type": "String", "description": "Value for T2 of CSF in millisecond for calibration - {default is based on 3T Field Strength}", "list": false, "name": "T2 CSF"}, {"command-line-flag": "--t2bl", "value-key": "[T2BL]", "optional": true, "id": "t2bl", "type": "String", "description": "Value for T2 of blood in millisecond for calibration - {default: 0}", "list": false, "name": "T2 Blood"}, {"command-line-flag": "--te", "value-key": "[TE]", "optional": true, "default-value": "", "id": "te", "type": "String", "description": "Echo time for readout in milliseconds - {default: 0}", "list": false, "name": "TE time"}, {"command-line-flag": "--cblip", "value-key": "[CBLIP]", "optional": true, "id": "cblip", "type": "File", "description": "Phase-encode-reversed (blipped) calibration image", "list": false, "name": "Blipped calibration"}, {"command-line-flag": "--pedir", "type": "String", "optional": true, "id": "pedir", "value-choices": ["x", "y", "z", "-x", "-y", "-z"], "value-key": "[PEDIR]", "description": "Phase encoding direction", "command-line-flag-separator": "=", "list": false, "name": "Direction"}, {"command-line-flag": "--echospacing", "value-key": "[ECHOSPACING]", "optional": true, "id": "echospacing", "type": "String", "description": "Effective EPI echo spacing (sometimes called dwell time) in seconds", "command-line-flag-separator": "=", "list": false, "name": "EPI"}, {"command-line-flag": "--pvcorr", "value-key": "[PVCORR]", "optional": true, "id": "pvcorr", "type": "Flag", "description": "Do partial volume correction", "list": false, "name": "Volume correction"}], "commandline": "if [[ -f \"[FSL_INFILE]\" ]]; then fsl_anat -i [FSL_INFILE] -o FSLANAT_OUT; FSLANAT='--fslanat=FSLANAT_OUT.anat'; elif [[ -d \"[FSLANAT]\" ]]; then FSLANAT=\"--fslanat=[FSLANAT]\"; else FSLANAT=''; fi && oxford_asl [INPUT_FILE] [OUTPUT_DIR] [MASK] [SPATIAL] [WP] [MC] [IAF] [IBF] [TIS] [TIIMG] [CASL] [ARTSUPP] [FIXBOLUS] [BOLUS] [BAT] [T1] [T1B] [SLICEDT] [SLICEBAND] [RPTS] $FSLANAT [S] [SBRAIN] [FASTSRC] [SENSCORR] [M0] [ALPHA] [C] [TR] [CMETHOD] [TE] [T2BL] [T2CSF] [CBLIP] [PEDIR] [ECHOSPACING] [PVCORR]; ", "name": "oxford_asl", "containerimage": {"image": "mcin/docker-fsl:latest", "index": "docker://", "type": "singularity"}, "outputfiles": [{"command-line-flag": "-o", "id": "outputs", "path-template": "[INPUT_FILE]", "value-key": "[OUTPUT_DIR]", "description": "Oxford asl Outputs", "path-template-stripped-extensions": [".nii.gz", ".nii"], "list": false, "name": "Oxford asl Outputs"}, {"optional": true, "id": "fsl_out", "path-template": "FSLANAT_OUT.anat", "description": "A folder containing the output files for fsl_anat. Includes outputs for the images, reorientation, cropping, bias correction, registration, brain extraction, and segmentation.", "list": false, "name": "FSL Anat Output folder"}], "groups": [{"id": "acquisition", "members": ["iaf", "ibf", "tis", "tiimg", "casl", "artsupp", "fixbolus", "bolus", "bat", "t1", "t1b", "slicedt", "sliceband", "rpts"], "name": "Acquisition specific/Data specific"}, {"id": "structural", "members": ["s", "sbrain", "fastsrc", "senscorr"], "name": "Structural image"}, {"id": "group_1", "name": "FSL Anat Structural data", "description": "Run a new FSL Anat or provide results folder of already executed FSL Anat. You can use either run FSL Anat on an image file or supply an existing folder with previously saved results of FSL Anat, but not both.", "mutually-exclusive": true, "members": ["fslanat", "infile"]}, {"id": "calibration", "members": ["m0", "alpha", "c", "tr", "cmethod", "te", "t2csf", "t2bl"], "name": "Calibration options"}, {"id": "distortion", "members": ["cblip", "echospacing", "pedir"], "name": "Distortion correction"}, {"id": "partial", "members": ["pvcorr"], "name": "Partial correction"}], "suggestedresources": {"ram": 4, "walltime-estimate": 6000}, "ark_id": "https://n2t.net/ark:/70798/p7rpqhj3k9rv766hc6", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.5889065", "title": "FMRIprepSingleSubject", "description": "fMRIprep is a functional magneticresonance image pre-processing pipeline that is designed to provide an easily accessible, state-of-the-art interface that is robust to differences in scan acquisition protocols and that requires minimal user input, while providing easily interpretable and comprehensive error and output reporting (https://fmriprep.readthedocs.io). NOTE: This descriptor is designed to integrate specifically with a CBRAIN installation. It takes as input a single subject according to the BIDs specification", "publicationdate": "2022-01-21", "deprecated": false, "downloads": 29, "author": "Poldrack lab", "version": "20.1.3", "doi": "10.5281/zenodo.5889065", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["neuroinformatics", "fmri"], "application-type": ["bids"]}, "suggestedresources": {"walltime-estimate": 172000, "cpu-cores": 4, "ram": 4}, "containerimage": {"image": "poldracklab/fmriprep:20.1.3", "index": "docker://", "type": "singularity"}, "url": "https://fmriprep.readthedocs.io", "inputs": [{"description": "subject folder for BIDS (folders name should be sub-XXXXX).", "id": "subject_dir", "optional": false, "name": "subject_dir", "value-key": "[SUBJECT_DIR]", "type": "File"}, {"description": "the output path for the outcomes of preprocessing and visual reports", "id": "output_dir_name", "optional": false, "name": "output_dir_name", "value-key": "[OUTPUT_DIR]", "type": "String"}, {"description": "The FreeSurfer license key file", "id": "fs_license_file", "optional": false, "name": "fs_license_file", "command-line-flag": "--fs-license-file", "value-key": "[FS_LICENSE]", "type": "File"}, {"description": "select a specific task to be processed", "id": "task_id", "optional": true, "name": "task_id", "command-line-flag": "-t", "value-key": "[TASK_ID]", "type": "String"}, {"description": "attempt to reduce memory usage (will increase disk usage in working directory)", "id": "low_mem", "optional": true, "name": "low_mem", "command-line-flag": "--low-mem", "value-key": "[LOW_MEM]", "type": "Flag"}, {"description": "nipype plugin configuration file", "id": "use_plugin", "optional": true, "name": "use_plugin", "command-line-flag": "--use-plugin", "value-key": "[USE_PLUGIN]", "type": "String"}, {"description": "run anatomical workflows only", "id": "anat_only", "optional": true, "name": "anat_only", "command-line-flag": "--anat-only", "value-key": "[ANAT_ONLY]", "type": "Flag"}, {"description": "generate boilerplate only", "id": "boilerplate", "optional": true, "name": "boilerplate", "command-line-flag": "--boilerplate", "value-key": "[BOILERPLATE]", "type": "Flag"}, {"description": "increases log verbosity for each occurence, debug level is -vvv", "id": "verbose_count", "optional": true, "name": "verbose_count", "command-line-flag": "-v", "value-key": "[VERBOSE_COUNT]", "type": "String"}, {"description": "ignore selected aspects of the input dataset to disable corresponding parts of the workflow (a space delimited list)", "id": "ignore", "command-line-flag": "--ignore", "list": true, "name": "ignore", "optional": true, "value-choices": ["fieldmaps", "slicetiming", "sbref"], "value-key": "[IGNORE]", "type": "String"}, {"description": "treat dataset as longitudinal - may increase runtime", "id": "longitudinal", "optional": true, "name": "longitudinal", "command-line-flag": "--longitudinal", "value-key": "[LONGITUDINAL]", "type": "Flag"}, {"description": "Degrees of freedom when registering BOLD to T1w images. 6 degrees (rotation and translation) are used by default.", "id": "bold2t1w_dof", "command-line-flag": "--bold2t1w-dof", "name": "bold2t1w_dof", "optional": true, "value-choices": [6, 9, 12], "default-value": 6, "value-key": "[BOLD2T1W_DOF]", "type": "Number"}, {"description": "Always use boundary-based registration (no goodness-of-fit checks)", "id": "use_bbr", "optional": true, "name": "use_bbr", "command-line-flag": "--force-bbr", "value-key": "[USE_BBR]", "type": "Flag"}, {"description": "Replace medial wall values with NaNs on functional GIFTI files. Only performed for GIFTI files mapped to a freesurfer subject (fsaverage or fsnative).", "id": "medial_surface_nan", "optional": true, "name": "medial_surface_nan", "command-line-flag": "--medial-surface-nan", "value-key": "[MEDIAL_SURFACE_NAN]", "type": "Flag"}, {"description": "add ICA_AROMA to your preprocessing stream", "id": "use_aroma", "optional": true, "name": "use_aroma", "command-line-flag": "--use-aroma", "value-key": "[USE_AROMA]", "type": "Flag"}, {"description": "Exact or maximum number of MELODIC components to estimate (positive = exact, negative = maximum)", "id": "aroma_melodic_dimensionality", "command-line-flag": "--aroma-melodic-dimensionality", "name": "aroma_melodic_dimensionality", "optional": true, "default-value": -200, "value-key": "[AROMA_MELODIC_DIMENSIONALITY]", "type": "Number"}, {"description": "select ANTs skull-stripping template (default: OASIS30ANTs))", "id": "skull_strip_template", "command-line-flag": "--skull-strip-template", "name": "skull_strip_template", "optional": true, "value-choices": ["OASIS30ANTs"], "default-value": "OASIS30ANTs", "value-key": "[SKULL_STRIP_TEMPLATE]", "type": "String"}, {"description": "do not use a random seed for skull-stripping - will ensure run-to-run replicability when used with --omp-nthreads 1", "id": "skull_strip_fixed_seed", "optional": true, "name": "skull_strip_fixed_seed", "command-line-flag": "--skull-strip-fixed-seed", "value-key": "[SKULL_STRIP_FIXED_SEED]", "type": "Flag"}, {"description": "fit a B-Spline field using least-squares (experimental)", "id": "fmap_bspline", "optional": true, "name": "fmap_bspline", "command-line-flag": "--fmap-bspline", "value-key": "[FMAP_BSPLINE]", "type": "Flag"}, {"description": "do not remove median (within mask) from fieldmap", "id": "fmap_no_demean", "optional": true, "name": "fmap_no_demean", "command-line-flag": "--fmap-no-demean", "value-key": "[FMAP_NO_DEMEAN]", "type": "Flag"}, {"description": "EXPERIMENTAL: Use fieldmap-free distortion correction", "id": "use_syn_sdc", "optional": true, "name": "use_syn_sdc", "command-line-flag": "--use-syn-sdc", "value-key": "[USE_SYN_SDC]", "type": "Flag"}, {"description": "EXPERIMENTAL/TEMPORARY: Use SyN correction in addition to fieldmap correction, if available", "id": "force_syn", "optional": true, "name": "force_syn", "command-line-flag": "--force-syn", "value-key": "[FORCE_SYN]", "type": "Flag"}, {"description": "disable sub-millimeter (hires) reconstruction", "id": "hires", "optional": true, "name": "hires", "command-line-flag": "--no-submm-recon", "value-key": "[HIRES]", "type": "Flag"}, {"description": "output BOLD files as CIFTI dtseries", "id": "cifti_output", "optional": true, "name": "cifti_output", "command-line-flag": "--cifti-output", "value-choices": ["91k", "170k"], "value-key": "[CIFTI_OUTPUT]", "type": "String"}, {"description": "disable FreeSurfer surface preprocessing. Note : `--no-freesurfer` is deprecated and will be removed in 1.2. Use `--fs-no-reconall` instead.", "id": "run_reconall", "optional": true, "name": "run_reconall", "command-line-flag": "--fs-no-reconall", "value-key": "[RUN_RECONALL]", "type": "Flag"}, {"description": "enable Nipype's resource monitoring to keep track of memory and CPU usage", "id": "resource_monitor", "optional": true, "name": "resource_monitor", "command-line-flag": "--resource-monitor", "value-key": "[RESOURCE_MONITOR]", "type": "Flag"}, {"description": "only generate reports, don't run workflows. This will only rerun report aggregation, not reportlet generation for specific nodes.", "id": "reports_only", "optional": true, "name": "reports_only", "command-line-flag": "--reports-only", "value-key": "[REPORTS_ONLY]", "type": "Flag"}, {"description": "Specify UUID of previous run, to include error logs in report. No effect without --reports-only.", "id": "run_uuid", "optional": true, "name": "run_uuid", "command-line-flag": "--run-uuid", "value-key": "[RUN_UUID]", "type": "String"}, {"description": "Write workflow graph.", "id": "write_graph", "optional": true, "name": "write_graph", "command-line-flag": "--write-graph", "value-key": "[WRITE_GRAPH]", "type": "Flag"}, {"description": "Force stopping on first crash, even if a work directory was specified.", "id": "stop_on_first_crash", "optional": true, "name": "stop_on_first_crash", "command-line-flag": "--stop-on-first-crash", "value-key": "[STOP_ON_FIRST_CRASH]", "type": "Flag"}, {"description": "Opt-out of sending tracking information of this run to the FMRIPREP developers. This information helps to improve FMRIPREP and provides an indicator of real world usage crucial for obtaining funding.", "id": "notrack", "optional": true, "name": "notrack", "command-line-flag": "--notrack", "value-key": "[NOTRACK]", "type": "Flag"}, {"description": "Use low-quality tools for speed - TESTING ONLY", "id": "sloppy", "optional": true, "name": "sloppy", "command-line-flag": "--sloppy", "value-key": "[SLOPPY]", "type": "Flag"}], "groups": [{"description": "Paramters used to define memory requirements and multithreading", "id": "memory_and_parallelism", "members": ["low_mem"], "name": "Memory and Parallel Control Parameters"}, {"description": "Diagnostic parameters for debugging fMRIprep", "id": "debugging", "members": ["verbose_count", "resource_monitor", "reports_only", "run_uuid", "stop_on_first_crash", "notrack", "write_graph", "sloppy"], "name": "Debugging Parameters"}, {"description": "Parameters that one should use at their own risk.", "id": "experimental", "members": ["use_syn_sdc", "force_syn"], "name": "Experimental Parameters"}], "name": "FMRIprepSingleSubject", "toolversion": "20.1.3", "custom": {"cbrain:readonly-input-files": true, "cbrain:author": "Natacha Beck <natacha.beck@mcgill.ca>"}, "outputfiles": [{"description": "This is the directory where the overall outputs are to be stored.", "optional": false, "id": "output_dir", "path-template": "[OUTPUT_DIR]", "name": "Output Directory"}], "commandline": "SUB_FULL_PATH=[SUBJECT_DIR]; SUBJECT_NAME=$(basename \"$SUB_FULL_PATH\"); FAKE_BIDS_DIR=fake_bids_dir; [[ \"$SUB_FULL_PATH\" != /* ]] && SUB_FULL_PATH=\"$PWD\"/\"$SUB_FULL_PATH\"; mkdir -p \"$FAKE_BIDS_DIR\"; ln -s \"$SUB_FULL_PATH\" \"$FAKE_BIDS_DIR\"/\"$SUBJECT_NAME\"; fmriprep \"$FAKE_BIDS_DIR\" [OUTPUT_DIR] participant --skip_bids_validation --participant_label \"$SUBJECT_NAME\" [TASK_ID] --nthreads 1 --omp-nthreads 1 --mem_mb 8192 [LOW_MEM] [USE_PLUGIN] [ANAT_ONLY] [BOILERPLATE] [VERBOSE_COUNT] [IGNORE] [LONGITUDINAL] [BOLD2T1W_DOF] [USE_BBR] [MEDIAL_SURFACE_NAN] [USE_AROMA] [AROMA_MELODIC_DIMENSIONALITY] [SKULL_STRIP_TEMPLATE] [SKULL_STRIP_FIXED_SEED] [FMAP_BSPLINE] [FMAP_NO_DEMEAN] [USE_SYN_SDC] [FORCE_SYN] [FS_LICENSE] [HIRES] [CIFTI_OUTPUT] [RUN_RECONALL] [RESOURCE_MONITOR] [REPORTS_ONLY] [RUN_UUID] [WRITE_GRAPH] [STOP_ON_FIRST_CRASH] [NOTRACK] [SLOPPY]; status=$?; test $status -eq 0 && rm -rf [OUTPUT_DIR]/freesurfer/fsaverage; bash -c \"exit $status\"", "ark_id": "https://n2t.net/ark:/70798/p7dtwktmd27s20b5qc", "platforms": [{"img": "/static/img/run_on_cbrain_green.png", "uri": "/cbrainredirect?cbrainurl=https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id%3D291"}]}, {"id": "zenodo.7387748", "title": "FreeSurfer-mris_preproc", "description": "Concatenate surface-based data with mris_preproc (https://surfer.nmr.mgh.harvard.edu/fswiki/mris_preproc).", "publicationdate": "2022-12-01", "deprecated": false, "downloads": 28, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.1.1", "doi": "10.5281/zenodo.7387704", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer-mris_preproc", "containerimage": {"index": "docker://", "image": "freesurfer/freesurfer:7.1.1", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; mris_preproc --fsgd [FSGD] --cache-in [CACHEIN] --target [TARGET] --hemi [HEMI] --out [OUT]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "fsgd", "id": "fsgd", "optional": false, "value-key": "[FSGD]", "description": "fsgd file", "type": "String"}, {"name": "cache-in", "id": "cachein", "optional": false, "value-key": "[CACHEIN]", "description": "cache-in", "type": "String"}, {"name": "target", "id": "target", "optional": false, "value-key": "[TARGET]", "description": "target", "type": "String"}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}, {"name": "out", "id": "out", "optional": false, "value-key": "[OUT]", "description": "output directory", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7245wg7z12dn35xcn", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.6338035", "title": "APPIANPET", "description": "APPIAN is an automated pipeline for user-friendly and reproducible analysis of positron emission tomography (PET) images with the aim of automating all processing steps up to the statistical analysis of measures derived from the final output images.", "publicationdate": "2022-03-08", "deprecated": false, "downloads": 28, "author": "Thomas Funck (https://github.com/tfunck)", "version": "1", "doi": "10.5281/zenodo.6338035", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "APPIANPET", "inputs": [{"name": "BIDS directory", "type": "File", "command-line-flag": "-s", "optional": false, "description": "The directory with the input dataset formatted according to the BIDS standard.", "id": "bids_dir", "value-key": "[BIDS_DIR]"}, {"name": "Output directory name", "type": "String", "optional": false, "description": "The directory where the output files should be stored.", "id": "output_dir_name", "value-key": "[OUTPUT_DIR]"}], "toolversion": "1", "outputfiles": [{"name": "Output directory", "command-line-flag": "-t", "optional": false, "description": "The directory where the output files should be stored.", "id": "output_dir", "path-template": "[OUTPUT_DIR]"}], "commandline": "mkdir [OUTPUT_DIR];python3 /opt/APPIAN/Launcher.py [BIDS_DIR] -t [OUTPUT_DIR]", "containerimage": {"type": "singularity", "image": "APPIAN-PET/APPIAN"}, "custom": {"cbrain:readonly-input-files": true, "cbrain:author": "Natacha Beck <natacha.beck@mcgill.ca>"}, "ark_id": "https://n2t.net/ark:/70798/p7kmknkk436bq0k7hp", "platforms": [{"img": "/static/img/run_on_cbrain_green.png", "uri": "/cbrainredirect?cbrainurl=https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id%3D220"}]}, {"id": "zenodo.7378416", "title": "FreeSurfer-long_mris_slopes", "description": "Prepare the data with long_mris_slopes for longitudinal two stage model (https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalTwoStageModel).", "publicationdate": "2022-11-28", "deprecated": false, "downloads": 27, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.1.1", "doi": "10.5281/zenodo.7372984", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer-long_mris_slopes", "containerimage": {"index": "docker://", "image": "freesurfer/freesurfer:7.1.1", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; long_mris_slopes --qdec [QDEC] --meas [MEASURE] --hemi [HEMI] --do-avg --do-rate --do-pc1 --do-pc1fit --do-spc --do-stack --do-label --time [TIME] --qcache fsaverage --sd $SUBJECTS_DIR --stack-avg [SAVG] --stack-rate [SRATE] --stack-pc1fit [SPC1FIT] --stack-pc1 [SPC1] --stack-spc [SSPC]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "qdec table", "id": "qdec", "optional": false, "value-key": "[QDEC]", "description": "qdec table", "type": "String"}, {"name": "measure", "id": "meas", "optional": false, "value-key": "[MEASURE]", "description": "measure", "type": "String", "value-choices": ["thickness", "volume"]}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}, {"name": "time", "id": "time", "optional": false, "value-key": "[TIME]", "description": "time variable in qdec table", "type": "String"}, {"name": "stack_avg", "id": "stack_avg", "optional": false, "value-key": "[SAVG]", "description": "Output stacked avg maps on <qtarget> for all fwhm levels", "type": "String"}, {"name": "stack_rate", "id": "stack_rate", "optional": false, "value-key": "[SRATE]", "description": "Output stacked rate maps on <qtarget> for all fwhm levels", "type": "String"}, {"name": "stack_pc1fit", "id": "stack_pc1fit", "optional": false, "value-key": "[SPC1FIT]", "description": "Output stacked pc1fit maps on <qtarget> for all fwhm levels", "type": "String"}, {"name": "stack_pc1", "id": "stack_pc1", "optional": false, "value-key": "[SPC1]", "description": "Output stacked pc1 maps on <qtarget> for all fwhm levels", "type": "String"}, {"name": "stack_spc", "id": "stack_spc", "optional": false, "value-key": "[SSPC]", "description": "Output stacked spc maps on <qtarget> for all fwhm levels", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p730nt25c0b3t7npcb", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.6515367", "title": "cbellum", "description": "Surface reconstruction of the cerebellum", "publicationdate": "2022-05-03", "deprecated": false, "downloads": 27, "author": "P\u00e9tur Helgi Einarsson", "version": "1", "doi": "10.5281/zenodo.6515367", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["boutiques", "bigbrain"]}, "toolversion": "1", "custom": {"cbrain:readonly-input-files": true, "cbrain:author": "Natacha Beck <natacha.beck@mcgill.ca>", "cbrain:integrator_modules": {"BoutiquesOutputFileTypeSetter": {"output_file_ply": "PlyFile", "output_file_npy": "NpyFile"}, "BoutiquesFileTypeVerifier": {"input_file": ["NpyFile"]}, "BoutiquesFileNameMatcher": {"input_file": "\\.npy$"}}}, "inputs": [{"description": "Path to the input volume file (.npy)", "type": "File", "id": "input_file", "command-line-flag": "-i", "optional": false, "value-key": "[INPUT]", "name": "Input volume file"}, {"description": "The number (int) of iterations to run.", "default-value": "1000", "type": "Number", "id": "nits", "command-line-flag": "--n-its", "optional": false, "value-key": "[NITS]", "name": "Number of iterations"}, {"description": "The interpolation value at each Jacobi iteration (0 < STEP_SIZE <= 1).", "exclusive-minimum": true, "type": "Number", "default-value": "0.5", "exclusive-maximum": false, "maximum": 1, "optional": false, "id": "step_size", "command-line-flag": "--step-size", "value-key": "[STEP_SIZE]", "minimum": 0, "name": "Step size"}, {"description": "If no input file is provided, the dimensions of the data is X x Y x Z.", "default-value": "X Y Z", "type": "String", "id": "dimension", "command-line-flag": "-dims", "optional": true, "value-key": "[DIMS]", "name": "Dimemsions"}, {"description": "The size of the band surrounding the boundary. The voxels within the distance of BAND_SIZE (>0) are used for the QP.", "exclusive-minimum": true, "type": "Number", "id": "band_size", "command-line-flag": "--band-size", "optional": true, "value-key": "[BAND_SIZE]", "minimum": 0, "name": "Band size"}, {"description": "The size of the band surrounding the boundary. The voxels within the distance of BAND_SIZE (>0) are used for the QP.", "value-choices": ["0", "6", "18", "26"], "type": "Number", "id": "boundary_nbrhood", "command-line-flag": "--boundary-nbrhood", "optional": true, "value-key": "[BOUNDARY_NBRHOOD]", "name": "Boundary nbrhood"}, {"description": "Use this flag if thin structures are supposed to be preserved.", "type": "Flag", "id": "preserve_thin", "command-line-flag": "--preserve-thin", "optional": true, "value-key": "[PRESERVE_THIN]", "name": "Preserve thin"}], "containerimage": {"index": "docker://", "type": "singularity", "image": "peturhelgi/cbellum"}, "suggestedresources": {"ram": 1, "walltime-estimate": 60, "cpu-cores": 1}, "outputfiles": [{"description": "Name for the mesh file generated by the program; the .ply extension will be added", "list": false, "optional": false, "path-template-stripped-extensions": [".npy"], "id": "output_file_ply", "command-line-flag": "-o", "path-template": "[INPUT]_res.ply", "value-key": "[OUTPUT_FILE_PLY]", "name": "Output mesh file"}, {"description": "Name for the emb file generated by the program", "list": false, "optional": false, "path-template-stripped-extensions": [".npy"], "id": "output_file_npy", "command-line-flag": "-o2", "path-template": "[INPUT]_res.npy", "value-key": "[OUTPUT_FILE_NPY]", "name": "Output emb file"}], "commandline": "/cerebellum/bin/build_mesh [INPUT] [OUTPUT_FILE_PLY] [OUTPUT_FILE_NPY] [DIMS] [NITS] [STEP_SIZE] [BAND_SIZE] [BOUNDARY_NBRHOOD] [PRESERVE_THIN]", "name": "cbellum", "ark_id": "https://n2t.net/ark:/70798/p7pm9kq4f97gh6ck1n", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.6338382", "title": "pcev", "description": "Principal component of explained variance (PCEV) is a statistical tool for the analysis of a multivariate response vector. It is a dimension-reduction technique, similar to Principal component analysis (PCA), that seeks to maximize the proportion of variance (in the response vector) being explained by a set of covariates.", "publicationdate": "2022-03-08", "deprecated": false, "downloads": 27, "author": "Greenwood Lab Montreal", "version": "1.0.0", "doi": "10.5281/zenodo.6338382", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["bioinformatics", "genetic"]}, "suggestedresources": {"walltime-estimate": 10000}, "onlineplatformurls": ["https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id=77"], "outputfiles": [{"list": false, "path-template": "[OUTPUT]", "name": "Output folder", "optional": false, "id": "folder_out", "description": "A folder containing the output files"}], "commandline": "bash run_pcevCBRAIN.sh [OUTPUT] [Y_DATA] [X_DATA] [C_DATA]", "toolversion": "1.0.0", "containerimage": {"image": "GreenwoodLab/pcev_pipelineCBRAIN:pcev_v1.0", "index": "shub://", "type": "singularity"}, "custom": {"cbrain:author": "Natacha Beck"}, "name": "pcev", "inputs": [{"list": false, "type": "File", "value-key": "[Y_DATA]", "name": "Y file", "optional": false, "id": "y_data", "description": "The name of the csv file corresponding to Y, the response matrix"}, {"list": false, "type": "File", "value-key": "[X_DATA]", "name": "X file", "optional": false, "id": "x_data", "description": "The covariates matrix"}, {"list": false, "type": "File", "value-key": "[C_DATA]", "name": "C file", "optional": true, "id": "c_data", "description": "The confounders matrix"}, {"list": false, "type": "String", "default-value": "pcev_output", "name": "Output directory", "optional": false, "value-key": "[OUTPUT]", "id": "outdir", "description": "Output directory name."}], "ark_id": "https://n2t.net/ark:/70798/p7c6z1qbz1d9d05v8j", "platforms": [{"img": "/static/img/run_on_cbrain_green.png", "uri": "/cbrainredirect?cbrainurl=https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id%3D77"}]}, {"id": "zenodo.6515351", "title": "mfannot", "description": "Automated annotation for mitochondrial and plastid genomes", "publicationdate": "2022-05-03", "deprecated": false, "downloads": 27, "author": "Pierre Rioux and Natacha Beck, Franz Bernd Lang Lab (https://github.com/BFL-lab)", "version": "1.36", "doi": "10.5281/zenodo.6515351", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["boutiques", "genetic"]}, "containerimage": {"type": "singularity", "image": "nbeck/mfannot:latest", "index": "docker://"}, "custom": {"cbrain:author": "Natacha Beck <natacha.beck@mcgill.ca>", "cbrain:readonly-input-files": true}, "commandline": "CWD=${PWD}; INPUT=$(echo [INPUT] | cut -f 1 -d '.'); mkdir [OUTPUT_DIR];  cp [INPUT] [OUTPUT_DIR]/${INPUT}; cd [OUTPUT_DIR]; mfannot [BLAST] [EL] [GENETIC] [INSERTION] [LIGHT] [MATRIX] [MAXIS] [MINES] [MINIS] [MINORFLEN] [OVERLAPCUT] [ORFOVORF] [ORFOVGENE] [PARTIAL] [LVLINTRON] [LVLMOT] [SQN] [TBL] ${INPUT}; cd ${CWD}", "suggestedresources": {"ram": 1, "walltime-estimate": 60, "cpu-cores": 1}, "outputfiles": [{"value-key": "[OUTPUT_DIR]", "optional": false, "path-template": "mfannot_res", "name": "The output directory", "id": "outfile"}], "inputs": [{"value-key": "[INPUT]", "type": "File", "name": "Input file", "id": "fasta", "optional": false, "description": "Input file (FASTA format)."}, {"value-key": "[GENETIC]", "type": "String", "command-line-flag": "-g", "name": "Genetic code", "id": "genetic", "value-choices": ["1", "2", "3", "4", "5", "6", "9", "10", "11", "12", "13", "14", "15", "16", "21", "22", "23"], "description": "1 =>  Standard (default)\n2 =>  Vertebrate Mitochondrial                  AGA=Ter(*),AGG=Ter(*),AUA=Met(M),UGA=Trp(W)\n3 =>  Yeast Mitochondrial                       ATA=Met(M),CTN=Thr(T),TGA=Trp(W)\n4 =>  Mold Mitochondrial                        TGA=Trp(W)\n5 =>  Invertebrate Mitochondrial                AGA=Ser(S),AGG=Ser(S),ATA=Met(M),TGA=Trp(W)\n6 =>  Ciliate Dasycladacean Hexamita Nuclear    TAA=Gln(Q),TAG=Gln(Q)\n9 =>  Echinoderm Flatworm Mitochondrial         AAA=Asn(N),AGA=Ser(S),AGG=Ser(S),TGA=Trp(W)\n10 => Euplotid Nuclear                          TGA=Cys(C)\n11 => Bacterial and Plant Plastid               \n12 => Alternative Yeast Nuclear                 CTG=Ser(S)\n13 => Ascidian Mitochondrial                    AGA=Gly(G),AGG=Gly(G),ATA=Met(M),TGA=Trp(W)\n14 => Alternative Flatworm Mitochondrial        AAA=Asn(N),AGA=Ser(S),AGG=Ser(S),TAA=Tyr(Y),TGA=Trp(W)\n15 => Blepharisma Macronuclear                  TAG=Gln(Q)\n16 => Chlorophycean Mitochondrial               TAG=Leu(L)\n21 => Trematode Mitochondrial                   TGA=Trp(W),ATA=Met(M),AGA=Ser(S),AGG=Ser(S)\n22 => Scenedesmus Obliquus Mitochondrial        TCA=Stop(*),TAG=Leu(L)\n23 => Thraustochytrium Mitochondrial            TTA=Stop(*)", "optional": true}, {"value-key": "[SQN]", "type": "Flag", "command-line-flag": "--sqn", "name": "Produce Sequin format", "id": "sqn", "optional": true}, {"value-key": "[TBL]", "type": "Flag", "command-line-flag": "--tbl", "name": "Generate a tbl Sequin file", "id": "tbl", "optional": true}, {"value-key": "[PARTIAL]", "type": "Flag", "command-line-flag": "--partial", "name": "Partial annotation", "id": "partial", "optional": true, "description": "Must be used when the genome his known to be partial or incomplete;\nthis will cause mfannot to only run a subset of all its built-in analysis."}, {"value-key": "[BLAST]", "type": "String", "command-line-flag": "--blast", "name": "Blast e-value cutoff", "id": "blast", "optional": true, "description": "Allows the user to set the minimum signifiant e-value for ORF threshold."}, {"value-key": "[EL]", "type": "String", "command-line-flag": "--emptyorflen", "name": "Empty ORF minimum length", "id": "emptyorflen", "optional": true, "description": "Allows the users to supply the cutoff value for an\nORF (in nuceotide) they must be multiple of 3, which is found\nnot to correspond to a gene.\nIt will instead appear in the Masterfile as ncorf (non\ncorresponding ORF)."}, {"value-key": "[INSERTION]", "type": "Number", "command-line-flag": "--insertion", "name": "Insertion", "id": "insertion", "optional": true, "description": "Allows the user to change the length of insertion in order to report them."}, {"value-key": "[LIGHT]", "type": "Flag", "command-line-flag": "--light", "name": "Endonuclease search", "id": "light", "optional": true, "description": "Don't perform endonuclease search, and don't search for all gene by HMM."}, {"value-key": "[MATRIX]", "type": "String", "command-line-flag": "--matrix", "name": "Matrix for BLAST", "id": "matrix", "optional": true, "description": "Allows the user to choose which alignment matrix is used during the blast.", "value-choices": ["BLOSUM45", "BLOSUM62", "PAM30", "PAM70"]}, {"value-key": "[MAXIS]", "type": "Number", "command-line-flag": "--maxintronsize", "name": "Maximum intron size", "id": "maxintronsize", "optional": true, "description": "Allows the user to modify the default maximum introns\nsize (in nucleotides). During annotation, ORFs are groupeds\ntogether to form a hypothetical protein. When this size is bigger,s\nthe gap can not be considered as an intron and the multiple ORFss\nform multiple hypothetical proteins."}, {"value-key": "[MINES]", "type": "Number", "command-line-flag": "--minexonsize", "name": "Minimum exon size", "id": "minexonsize", "optional": true, "description": "Allows the user to modify the default minimum exon\nsize (in nucleotides) that mfannot uses during internal structure\nprediction. This value should be an integer."}, {"value-key": "[MINIS]", "type": "Number", "command-line-flag": "--minintronsize", "name": "Minimum intron size", "id": "minintronsize", "optional": true, "description": "Allows the user to modify the default minimum intron\nsize (in nucleotides) that mfannot uses during internal structure\nprediction. This value should be an integer."}, {"value-key": "[MINORFLEN]", "type": "Number", "command-line-flag": "--minintronsize", "name": "Minimum ORF length", "id": "minorflen", "optional": true, "description": "Allows the user to choose the size of the minumum ORFs\n(in amino acids) that are produced using Flip. This value must be\nan integer."}, {"value-key": "[OVERLAPCUT]", "type": "Number", "command-line-flag": "--overlapcut", "name": "Minumum ORF length", "id": "overlapcut", "maximum": 100, "minimum": 0, "optional": true, "description": "Cutoff that represents the permitted overlapping\nproportion of a non-corresponding ORF that overlaps a predicted\ngene in nucleotide or on other non-corresponding ORF, value in \npercent."}, {"value-key": "[ORFOVORF]", "type": "Number", "command-line-flag": "--orfOVorf", "name": "Overlap between ORFs", "id": "orfOVorf", "optional": true, "description": "Special case, 2 orfs is overlapping but both of them make under\n Xaa of length, annotate the 2 ORFs."}, {"value-key": "[ORFOVGENE]", "type": "Number", "command-line-flag": "--orfOVgene", "name": "ORF overlap gene", "id": "orfOVgene", "optional": true, "description": "Special case, 1 orf is overlapping a gene and make Xaa of length\nannotate this one."}, {"value-key": "[LVLINTRON]", "type": "String", "command-line-flag": "--lvlintron", "name": "Level for introns identification", "id": "lvlintron", "optional": true, "description": "1 : run RNASpinner in all intragenic introns and check for rnl and rns introns.\nDefault 2 : run RNASpinner on whole genome.", "value-choices": ["1", "2"]}, {"value-key": "[LVLMOT]", "type": "String", "command-line-flag": "--lvlmot", "name": "Level of motif identification", "id": "lvlmot", "optional": true, "description": "Default 0 : run mfannot without motifs identification.\nIf is 1   : run only motifs identification.\nIf is 2   : run mfannot with motifs identification'.", "value-choices": ["0", "1", "2"]}], "name": "mfannot", "toolversion": "1.36", "groups": [{"members": ["blast", "emptyorflen", "insertion", "light", "matrix", "maxintronsize", "minexonsize", "minintronsize", "minorflen", "overlapcut", "orfOVorf", "orfOVgene", "lvlintron", "lvlmot"], "name": "Advanced options.", "id": "advanced"}], "ark_id": "https://n2t.net/ark:/70798/p7j7dh5rd478r20kk0", "platforms": [{"img": "/static/img/run_on_cbrain_green.png", "uri": "/cbrainredirect?cbrainurl=https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id%3D387"}]}, {"id": "zenodo.7332026", "title": "FreeSurfer-Recon-all-base", "description": "create an unbiased template from all time points for each subject and process it with recon-all -base: (https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalProcessing).", "publicationdate": "2022-11-16", "deprecated": false, "downloads": 26, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.1.1", "doi": "10.5281/zenodo.7332026", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "outputfiles": [{"name": "Output", "optional": false, "description": "output directory", "id": "output", "path-template": "[OUTPUTDIR]"}], "name": "FreeSurfer-Recon-all-base", "containerimage": {"index": "docker://", "image": "freesurfer/freesurfer:7.1.1", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; recon-all -base [OUTPUTDIR] -tp [TP1] -tp [TP2] -all", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "Output name", "optional": false, "value-key": "[OUTPUTDIR]", "type": "String", "id": "outputdir"}, {"name": "timepoint_1", "optional": false, "value-key": "[TP1]", "description": "Input directory timepoint 1", "type": "String", "id": "tp1"}, {"name": "timepoint_2", "optional": false, "value-key": "[TP2]", "description": "Input directory timepoint 2", "type": "String", "id": "tp2"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p73mtkn690hzv9j42n", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.6081609", "title": "hippunfold", "description": "BIDS App for Hippocampal AutoTop (automated hippocampal unfolding and subfield segmentation)", "publicationdate": "2022-02-14", "deprecated": false, "downloads": 26, "author": "Khan Computational Imaging Lab ", "version": "1.0.0", "doi": "10.5281/zenodo.6081609", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["boutiques"]}, "inputs": [{"description": "subject folder for BIDS (folders name should be sub-XXXXX).", "value-key": "[SUBJECT_DIR]", "optional": false, "type": "File", "name": "subject_dir", "id": "subject_dir"}, {"default-value": ["T2w"], "description": "Type of image to run hippunfold on, prefixed\nwith seg will import an existing hippocampal tissue\nsegmentation from that space, instead of running\nneural network (default: ['T2w'])", "value-key": "[MODALITY]", "list": true, "command-line-flag": "--modality", "value-choices": ["T1w", "T2w", "hippb500", "dwi", "segT1w", "segT2w", "cropseg"], "optional": true, "type": "String", "name": "modality", "id": "modality"}, {"description": "Path to the derivatives folder (e.g. for finding manual segs) (default: False)", "value-key": "[DERIVATIVES]", "command-line-flag": "--derivatives", "optional": true, "type": "File", "name": "derivatives", "id": "derivatives"}, {"description": "Set this flag if your inputs (e.g. T2w, dwi) are already pre-processed (default: False)", "value-key": "[SKIP_PREPROC]", "command-line-flag": "--skip_preproc", "optional": true, "type": "Flag", "name": "skip_preproc", "id": "skip_preproc"}, {"description": "Set this flag if your inputs (e.g. T2w, dwi) are already registered to T1w space (default: False)", "value-key": "[SKIP_COREG]", "command-line-flag": "--skip_coreg", "optional": true, "type": "Flag", "name": "skip_coreg", "id": "skip_coreg"}, {"description": "Set this flag to skip post-processing template injection into CNN segmentation (default: False)", "value-key": "[SKIP_INJECT_TEMPLATE_LABELS]", "command-line-flag": "--skip_inject_template_labels", "optional": true, "type": "Flag", "name": "skip_inject_template_labels", "id": "skip_inject_template_labels"}, {"description": "Scales the default smoothing sigma for gradient and warp in template shape injection. Using a value higher than 1 will use result in a smoother warp, and greater capacity to patch larger holes in segmentations. Try setting to 2 if nnunet segmentations have large holes. Note: the better solution is to re-train network on the data you are using (default: 1.0)", "value-key": "[INJECT_TEMPLATE_SMOOTHING_FACTOR]", "command-line-flag": "--inject-template-smoothing-factor", "optional": true, "type": "Number", "name": "inject_template_smoothing_factor", "id": "inject_template_smoothing_factor"}, {"description": "Use rigid instead of affine for registration to\ntemplate. Try this if your images are reduced FOV\n(default: False)", "value-key": "[RIGID_REG_TEMPLATE]", "command-line-flag": "--rigid_reg_template", "optional": true, "type": "Flag", "name": "rigid_reg_template", "id": "rigid_reg_template"}, {"description": "Use if input data is already in space-CITI168\n(default: False)", "value-key": "[NO_REG_TEMPLATE]", "command-line-flag": "--no_reg_template", "optional": true, "type": "Flag", "name": "no_reg_template", "id": "no_reg_template"}, {"description": "Set the template to use for registration to coronal oblique. (default: \u201cCITI168\u201d)", "value-key": "[TEMPLATE]", "command-line-flag": "--template", "value-choices": ["CITI168", "dHCP"], "optional": true, "type": "String", "name": "template", "id": "template"}, {"description": "Use T1w to register to template space, instead of the segmentation modality. Note: this was the default behavior prior to v1.0.0. (default: False)", "value-key": "[T1_REG_TEMPLATE]", "command-line-flag": "--t1_reg_template", "optional": true, "type": "Flag", "name": "t1_reg_template", "id": "t1_reg_template"}, {"description": "Disable test-time augmentation for nnU-net inference, speeds up inference by 8x, at expense of accuracy (default: False)", "value-key": "[NNUNET_DISABLE_TTA]", "command-line-flag": "--nnunet_disable_tta", "optional": true, "type": "Flag", "name": "nnunet_disable_tta", "id": "nnunet_disable_tta"}, {"default-value": "native", "description": "Sets the output space for results", "value-key": "[OUTPUT_SPACES]", "command-line-flag": "--output_spaces", "value-choices": ["native", "T1w"], "optional": true, "type": "String", "name": "output_spaces", "id": "output_spaces"}, {"default-value": ["0p5mm"], "description": "Sets the output vertex density for results. Options\ncorrespond to approximate vertex spacings of 0.5mm,\n1.0mm, and 2.0mm, respectively, with the 32k vertices\noption having unequal vertex spacing. (default: ['7k','2k'])", "value-key": "[OUTPUT_DENSITY]", "list": true, "command-line-flag": "--output_density", "value-choices": ["0p5mm", "1mm", "2mm", "unfoldiso"], "optional": true, "type": "String", "name": "output_density", "id": "output_density"}, {"default-value": ["L", "R"], "description": "Hemisphere(s) to process (default: ['L', 'R'])", "value-key": "[HEMI]", "list": true, "command-line-flag": "--hemi", "value-choices": ["L", "R"], "optional": true, "type": "String", "name": "hemi", "id": "hemi"}, {"default-value": "equivolume", "description": "Method to use for laminar coordinates. Equivolume uses\nequivolumetric layering from Waehnert et al 2014\n(Nighres implementation). (default: ['equivolume'])", "value-key": "[LAMINAR_COORDS_METHOD]", "command-line-flag": "--laminar_coords_method", "value-choices": ["laplace", "equivolume"], "optional": true, "type": "String", "name": "laminar_coords_method", "id": "laminar_coords_method"}, {"description": "Keep work folder intact instead of archiving it for each subject (default: False)", "value-key": "[KEEP_WORK]", "command-line-flag": "--keep_work", "optional": true, "type": "Flag", "name": "keep_work", "id": "keep_work"}, {"description": "Force nnunet model to use (expert option). (default: False)", "value-key": "[FORCE_NNUNET_MODEL]", "command-line-flag": "--force-nnunet-model", "value-choices": ["T1w", "T2w", "T1T2w", "b1000", "trimodal", "hippb500", "neonateT1w"], "optional": true, "type": "String", "name": "force_nnunet_model", "id": "force_nnunet_model"}], "groups": [{"members": ["modality", "derivatives", "skip_preproc", "skip_coreg", "skip_inject_template_labels", "inject_template_smoothing_factor", "rigid_reg_template", "no_reg_template", "template", "t1_reg_template", "nnunet_disable_tta", "output_spaces", "output_density", "hemi", "laminar_coords_method", "keep_work", "force_nnunet_model"], "name": "snakebids", "id": "snakebids"}], "suggestedresources": {"walltime-estimate": 7200, "ram": 8, "cpu-cores": 1}, "toolversion": "1.0.0", "outputfiles": [{"path-template": "[SUBJECT_DIR]_res", "description": "The output of the command", "value-key": "[OUTPUT_DIR]", "optional": false, "id": "output_dir", "name": "Output dir", "list": false}], "custom": {"cbrain:readonly-input-files": true, "cbrain:author": "Natacha Beck <natacha.beck@mcgill.ca>", "cbrain:integrator_modules": {"BoutiquesBidsSingleSubjectMaker": "subject_dir", "BoutiquesOutputFileTypeSetter": {"output_dir": "HippunfoldOutput"}, "BoutiquesFileTypeVerifier": {"subject_dir": ["BidsSubject"]}, "BoutiquesFileNameMatcher": {"subject_dir": "^sub-[a-zA-Z0-9_]+$"}}}, "commandline": "hippunfold [SUBJECT_DIR] [OUTPUT_DIR] participant [MODALITY] [DERIVATIVES] [SKIP_PREPROC] [SKIP_COREG] [SKIP_INJECT_TEMPLATE_LABELS] [INJECT_TEMPLATE_SMOOTHING_FACTOR] [RIGID_REG_TEMPLATE] [NO_REG_TEMPLATE] [TEMPLATE] [T1_REG_TEMPLATE] [NNUNET_DISABLE_TTA] [OUTPUT_SPACES] [OUTPUT_DENSITY] [HEMI] [LAMINAR_COORDS_METHOD] [KEEP_WORK] [FORCE_NNUNET_MODEL] -c1", "containerimage": {"index": "docker://", "type": "singularity", "image": "khanlab/hippunfold:v1.0.0"}, "name": "hippunfold", "ark_id": "https://n2t.net/ark:/70798/p7gfr2s28174q6xbbv", "platforms": [{"img": "/static/img/run_on_cbrain_green.png", "uri": "/cbrainredirect?cbrainurl=https://portal.cbrain.mcgill.ca/userfiles?prepare_tool_id%3D375"}]}, {"id": "zenodo.7339689", "title": "FreeSurfer-Recon-all-long", "description": "-long longitudinally process all timepoints with recon-all -long: (https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalProcessing).", "publicationdate": "2022-11-20", "deprecated": false, "downloads": 23, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.1.1", "doi": "10.5281/zenodo.7339689", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer-Recon-all-long", "containerimage": {"index": "docker://", "image": "freesurfer/freesurfer:7.1.1", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; recon-all -long [TP] [BASE] -all", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "timepoint", "id": "tp", "optional": false, "value-key": "[TP]", "description": "input timepoint", "type": "String"}, {"name": "base template", "id": "base", "optional": false, "value-key": "[BASE]", "description": "subject template", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p78gh8wmj1hjf6zh1n", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7779113", "title": "BraTSPipeline", "description": "Contact: software@cbica.upenn.edu. Copyright  (c) 2022 University of Pennsylvania. All rights reserved. See https://www.med.upenn.edu/cbica/software-agreement.html", "publicationdate": "2023-03-28", "deprecated": false, "downloads": 23, "author": "Sorina Pop", "version": "1.8.1", "doi": "10.5281/zenodo.7779113", "schemaversion": "0.5", "container": "docker", "tags": "Boutiques", "toolversion": "1.8.1", "name": "BraTSPipeline", "commandline": "/opt/captk/1.8.1/usr/bin/BraTSPipeline [T1C] [T1] [T2] [Fl] -o [OD] [SK] [BT] [PI]; ls -la [OD]; tar -czvf [RESULTS] [OD]", "containerimage": {"image": "docker.io/cbica/captk:2021.03.29", "type": "docker"}, "inputs": [{"command-line-flag": "-t1c", "description": "Input structural T1-weighted post-contrast image", "value-key": "[T1C]", "type": "File", "list": false, "optional": false, "id": "t1ceImage", "name": "t1ceImage"}, {"command-line-flag": "-t1", "description": "Input structural T1-weighted pre-contrast image", "value-key": "[T1]", "type": "File", "list": false, "optional": false, "id": "t1Image", "name": "t1Image"}, {"command-line-flag": "-t2", "description": "Input structural T2-weighted contrast image", "value-key": "[T2]", "type": "File", "list": false, "optional": false, "id": "t2Image", "name": "t2Image"}, {"command-line-flag": "-fl", "description": "Input structural FLAIR contrast image", "value-key": "[Fl]", "type": "File", "list": false, "optional": false, "id": "flImage", "name": "flImage"}, {"description": "Application output directory for final output", "value-key": "[OD]", "type": "String", "list": false, "optional": false, "id": "appliOutputDir", "name": "appliOutputDir"}, {"command-line-flag": "-s", "description": "Flag whether to skull strip or not. Defaults to 1. This uses DeepMedic: https://cbica.github.io/CaPTk/seg_DL.html", "default-value": 1, "value-key": "[SK]", "type": "Number", "value-choices": [0, 1], "optional": false, "id": "skullStrip", "name": "skullStrip"}, {"command-line-flag": "-b", "description": "Flag whether to segment brain tumors or not. Defaults to 1. This uses DeepMedic: https://cbica.github.io/CaPTk/seg_DL.html", "default-value": 1, "value-key": "[BT]", "type": "Number", "value-choices": [0, 1], "optional": false, "id": "brainTumor", "name": "brainTumor"}, {"command-line-flag": "-p", "description": "Patient ID to pre-pend to final output file names. If empty, final output is of the form ${modality}_to_SRI.nii.gz", "value-key": "[PI]", "type": "String", "list": false, "optional": true, "id": "patientID", "name": "patientID"}], "outputfiles": [{"description": "Output archive", "value-key": "[RESULTS]", "id": "output_archive", "optional": false, "path-template": "[OD].tar.gz", "name": "Output archive"}], "ark_id": "https://n2t.net/ark:/70798/p7985gzhc31672pj30", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7411893", "title": "FreeSurfer-mri_glmfit-sim", "description": "Performs general linear model (GLM) analysis in the volume or the surface with correction for multiple comparisons (https://surfer.nmr.mgh.harvard.edu/fswiki/mri_glmfit).", "publicationdate": "2022-12-07", "deprecated": false, "downloads": 23, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.1.1", "doi": "10.5281/zenodo.7411893", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer-mri_glmfit-sim", "containerimage": {"index": "docker://", "image": "freesurfer/freesurfer:7.1.1", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; mri_glmfit-sim --glmdir [DIR] --cache [CACHE_abs] abs --cwp [CWP] --2spaces", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "glm_dir", "id": "dir", "optional": false, "value-key": "[DIR]", "description": "glm directory", "type": "String"}, {"name": "CACHE_abs", "id": "CACHE_abs", "optional": false, "value-key": "[CACHE_abs]", "description": "vertex-wise cluster threshold for both contrasts", "type": "String"}, {"name": "cwp", "id": "cwp", "optional": false, "value-key": "[CWP]", "description": "cluster-wise p-threshold", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p73k2mp391h2m9cn8q", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7411530", "title": "FreeSurfer-mri_glmfit", "description": "Performs general linear model (GLM) analysis in the volume or the surface (https://surfer.nmr.mgh.harvard.edu/fswiki/mri_glmfit).", "publicationdate": "2022-12-07", "deprecated": false, "downloads": 23, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.1.1", "doi": "10.5281/zenodo.7411530", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer-mri_glmfit", "containerimage": {"index": "docker://", "image": "freesurfer/freesurfer:7.1.1", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; mri_glmfit --fsgd [FSGD] --glmdir [DIR] --y [INPUT] --surf fsaverage [HEMI] [CON]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "fsgd", "id": "fsgd", "optional": false, "value-key": "[FSGD]", "description": "fsgd file", "type": "String"}, {"name": "output_dir", "id": "outdir", "optional": false, "value-key": "[DIR]", "description": "output directory", "type": "String"}, {"name": "input", "id": "inputdata", "optional": false, "value-key": "[INPUT]", "description": "input file", "type": "String"}, {"name": "contrasts", "id": "con", "optional": false, "value-key": "[CON]", "description": "please specify contrasts with --C flag between each input", "type": "String"}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7jq600xw0gws8dh13", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7411856", "title": "FreeSurfer-mri_glmfit_3con", "description": "Performs general linear model (GLM) analysis in the volume or the surface (https://surfer.nmr.mgh.harvard.edu/fswiki/mri_glmfit).", "publicationdate": "2022-12-07", "deprecated": false, "downloads": 22, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.1.1", "doi": "10.5281/zenodo.7411856", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer-mri_glmfit_3con", "containerimage": {"index": "docker://", "image": "freesurfer/freesurfer:7.1.1", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; mri_glmfit --fsgd [FSGD] --glmdir [DIR] --y [INPUT] --surf fsaverage [HEMI] --C [CON1] --C [CON2] --C [CON3]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "fsgd", "id": "fsgd", "optional": false, "value-key": "[FSGD]", "description": "fsgd file", "type": "String"}, {"name": "output_dir", "id": "outdir", "optional": false, "value-key": "[DIR]", "description": "output directory", "type": "String"}, {"name": "input", "id": "inputdata", "optional": false, "value-key": "[INPUT]", "description": "input file", "type": "String"}, {"name": "contrast 1", "id": "con1", "optional": false, "value-key": "[CON1]", "description": "please specify contrasts 1", "type": "String"}, {"name": "contrast 2", "id": "con2", "optional": false, "value-key": "[CON2]", "description": "please specify contrasts 2", "type": "String"}, {"name": "contrast 3", "id": "con3", "optional": false, "value-key": "[CON3]", "description": "please specify contrasts 3", "type": "String"}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7v4qkqvg8tdx843sr", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.10306720", "title": "FLIRT 6.0.4 fuzzy", "description": "A fuzzy (https://github.com/verificarlo/fuzzy) version of FSL FLIRT, as implemented in Nipype (module: nipype.interfaces.fsl, interface: FLIRT).", "publicationdate": "2023-12-08", "deprecated": false, "downloads": 21, "author": "Nipype (interface), Oxford Centre for Functional MRI of the Brain (FMRIB) (tool)", "version": "1.0.0", "doi": "10.5281/zenodo.10306720", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "fmri"], "source": "nipype-interface"}, "name": "FLIRT 6.0.4 fuzzy", "commandline": "flirt [ANGLE_REP] [APPLY_ISOXFM] [APPLY_XFM] [BBRSLOPE] [BBRTYPE] [BGVALUE] [BINS] [COARSE_SEARCH] [COST] [COST_FUNC] [DATATYPE] [DOF] [ECHOSPACING] [FIELDMAP] [FIELDMAPMASK] [FINE_SEARCH] [FORCE_SCALING] [IN_FILE] [IN_MATRIX_FILE] [IN_WEIGHT] [INTERP] [MIN_SAMPLING] [NO_CLAMP] [NO_RESAMPLE] [NO_RESAMPLE_BLUR] [NO_SEARCH] [PADDING_SIZE] [PEDIR] [REF_WEIGHT] [REFERENCE] [RIGID2D] [SCHEDULE] [SEARCHR_X] [SEARCHR_Y] [SEARCHR_Z] [SINC_WIDTH] [SINC_WINDOW] [USES_QFORM] [VERBOSE] [WM_SEG] [WMCOORDS] [WMNORMS] [OUT_FILE] [OUT_MATRIX_FILE]", "inputs": [{"id": "angle_rep", "name": "Angle rep", "type": "String", "value-key": "[ANGLE_REP]", "command-line-flag": "-anglerep", "description": "'quaternion' or 'euler'. Representation of rotation angles.", "optional": true, "value-choices": ["quaternion", "euler"]}, {"id": "apply_isoxfm", "name": "Apply isoxfm", "type": "Number", "value-key": "[APPLY_ISOXFM]", "command-line-flag": "-applyisoxfm", "description": "A float. As applyxfm but forces isotropic resampling.", "optional": true}, {"id": "apply_xfm", "name": "Apply xfm", "type": "Flag", "value-key": "[APPLY_XFM]", "command-line-flag": "-applyxfm", "description": "A boolean. Apply transformation supplied by in_matrix_file or uses_qform to use the affine matrix stored in the reference header.", "optional": true}, {"id": "bbrslope", "name": "Bbrslope", "type": "Number", "value-key": "[BBRSLOPE]", "command-line-flag": "-bbrslope", "description": "A float. Value of bbr slope.", "optional": true}, {"id": "bbrtype", "name": "Bbrtype", "type": "String", "value-key": "[BBRTYPE]", "command-line-flag": "-bbrtype", "description": "'signed' or 'global_abs' or 'local_abs'. Type of bbr cost function: signed [default], global_abs, local_abs.", "optional": true, "value-choices": ["signed", "global_abs", "local_abs"]}, {"id": "bgvalue", "name": "Bgvalue", "type": "Number", "value-key": "[BGVALUE]", "command-line-flag": "-setbackground", "description": "A float. Use specified background value for points outside fov.", "optional": true}, {"id": "bins", "name": "Bins", "type": "Number", "integer": true, "value-key": "[BINS]", "command-line-flag": "-bins", "description": "An integer (int or long). Number of histogram bins.", "optional": true}, {"id": "coarse_search", "name": "Coarse search", "type": "Number", "integer": true, "value-key": "[COARSE_SEARCH]", "command-line-flag": "-coarsesearch", "description": "An integer (int or long). Coarse search delta angle.", "optional": true}, {"id": "cost", "name": "Cost", "type": "String", "value-key": "[COST]", "command-line-flag": "-cost", "description": "'mutualinfo' or 'corratio' or 'normcorr' or 'normmi' or 'leastsq' or 'labeldiff' or 'bbr'. Cost function.", "optional": true, "value-choices": ["mutualinfo", "corratio", "normcorr", "normmi", "leastsq", "labeldiff", "bbr"]}, {"id": "cost_func", "name": "Cost func", "type": "String", "value-key": "[COST_FUNC]", "command-line-flag": "-searchcost", "description": "'mutualinfo' or 'corratio' or 'normcorr' or 'normmi' or 'leastsq' or 'labeldiff' or 'bbr'. Cost function.", "optional": true, "value-choices": ["mutualinfo", "corratio", "normcorr", "normmi", "leastsq", "labeldiff", "bbr"]}, {"id": "datatype", "name": "Datatype", "type": "String", "value-key": "[DATATYPE]", "command-line-flag": "-datatype", "description": "'char' or 'short' or 'int' or 'float' or 'double'. Force output data type.", "optional": true, "value-choices": ["char", "short", "int", "float", "double"]}, {"id": "dof", "name": "Dof", "type": "Number", "integer": true, "value-key": "[DOF]", "command-line-flag": "-dof", "description": "An integer (int or long). Number of transform degrees of freedom.", "optional": true}, {"id": "echospacing", "name": "Echospacing", "type": "Number", "value-key": "[ECHOSPACING]", "command-line-flag": "-echospacing", "description": "A float. Value of epi echo spacing - units of seconds.", "optional": true}, {"id": "fieldmap", "name": "Fieldmap", "type": "File", "value-key": "[FIELDMAP]", "command-line-flag": "-fieldmap", "description": "A file name. Fieldmap image in rads/s - must be already registered to the reference image.", "optional": true}, {"id": "fieldmapmask", "name": "Fieldmapmask", "type": "File", "value-key": "[FIELDMAPMASK]", "command-line-flag": "-fieldmapmask", "description": "A file name. Mask for fieldmap image.", "optional": true}, {"id": "fine_search", "name": "Fine search", "type": "Number", "integer": true, "value-key": "[FINE_SEARCH]", "command-line-flag": "-finesearch", "description": "An integer (int or long). Fine search delta angle.", "optional": true}, {"id": "force_scaling", "name": "Force scaling", "type": "Flag", "value-key": "[FORCE_SCALING]", "command-line-flag": "-forcescaling", "description": "A boolean. Force rescaling even for low-res images.", "optional": true}, {"id": "in_file", "name": "In file", "type": "File", "value-key": "[IN_FILE]", "command-line-flag": "-in", "description": "An existing file name. Input file.", "optional": false}, {"id": "in_matrix_file", "name": "In matrix file", "type": "File", "value-key": "[IN_MATRIX_FILE]", "command-line-flag": "-init", "description": "A file name. Input 4x4 affine matrix.", "optional": true}, {"id": "in_weight", "name": "In weight", "type": "File", "value-key": "[IN_WEIGHT]", "command-line-flag": "-inweight", "description": "An existing file name. File for input weighting volume.", "optional": true}, {"id": "interp", "name": "Interp", "type": "String", "value-key": "[INTERP]", "command-line-flag": "-interp", "description": "'trilinear' or 'nearestneighbour' or 'sinc' or 'spline'. Final interpolation method used in reslicing.", "optional": true, "value-choices": ["trilinear", "nearestneighbour", "sinc", "spline"]}, {"id": "min_sampling", "name": "Min sampling", "type": "Number", "value-key": "[MIN_SAMPLING]", "command-line-flag": "-minsampling", "description": "A float. Set minimum voxel dimension for sampling.", "optional": true}, {"id": "no_clamp", "name": "No clamp", "type": "Flag", "value-key": "[NO_CLAMP]", "command-line-flag": "-noclamp", "description": "A boolean. Do not use intensity clamping.", "optional": true}, {"id": "no_resample", "name": "No resample", "type": "Flag", "value-key": "[NO_RESAMPLE]", "command-line-flag": "-noresample", "description": "A boolean. Do not change input sampling.", "optional": true}, {"id": "no_resample_blur", "name": "No resample blur", "type": "Flag", "value-key": "[NO_RESAMPLE_BLUR]", "command-line-flag": "-noresampblur", "description": "A boolean. Do not use blurring on downsampling.", "optional": true}, {"id": "no_search", "name": "No search", "type": "Flag", "value-key": "[NO_SEARCH]", "command-line-flag": "-nosearch", "description": "A boolean. Set all angular searches to ranges 0 to 0.", "optional": true}, {"id": "padding_size", "name": "Padding size", "type": "Number", "integer": true, "value-key": "[PADDING_SIZE]", "command-line-flag": "-paddingsize", "description": "An integer (int or long). For applyxfm: interpolates outside image by size.", "optional": true}, {"id": "pedir", "name": "Pedir", "type": "Number", "integer": true, "value-key": "[PEDIR]", "command-line-flag": "-pedir", "description": "An integer (int or long). Phase encode direction of epi - 1/2/3=x/y/z & -1/-2/-3=-x/-y/-z.", "optional": true}, {"id": "ref_weight", "name": "Ref weight", "type": "File", "value-key": "[REF_WEIGHT]", "command-line-flag": "-refweight", "description": "An existing file name. File for reference weighting volume.", "optional": true}, {"id": "reference", "name": "Reference", "type": "File", "value-key": "[REFERENCE]", "command-line-flag": "-ref", "description": "An existing file name. Reference file.", "optional": false}, {"id": "rigid2D", "name": "Rigid2d", "type": "Flag", "value-key": "[RIGID2D]", "command-line-flag": "-2D", "description": "A boolean. Use 2d rigid body mode - ignores dof.", "optional": true}, {"id": "schedule", "name": "Schedule", "type": "File", "value-key": "[SCHEDULE]", "command-line-flag": "-schedule", "description": "An existing file name. Replaces default schedule.", "optional": true}, {"id": "searchr_x", "name": "Searchr x", "type": "Number", "list": true, "integer": true, "min-list-entries": 2, "max-list-entries": 2, "value-key": "[SEARCHR_X]", "command-line-flag": "-searchrx", "description": "A list of from 2 to 2 items which are an integer (int or long). Search angles along x-axis, in degrees.", "optional": true}, {"id": "searchr_y", "name": "Searchr y", "type": "Number", "list": true, "integer": true, "min-list-entries": 2, "max-list-entries": 2, "value-key": "[SEARCHR_Y]", "command-line-flag": "-searchry", "description": "A list of from 2 to 2 items which are an integer (int or long). Search angles along y-axis, in degrees.", "optional": true}, {"id": "searchr_z", "name": "Searchr z", "type": "Number", "list": true, "integer": true, "min-list-entries": 2, "max-list-entries": 2, "value-key": "[SEARCHR_Z]", "command-line-flag": "-searchrz", "description": "A list of from 2 to 2 items which are an integer (int or long). Search angles along z-axis, in degrees.", "optional": true}, {"id": "sinc_width", "name": "Sinc width", "type": "Number", "integer": true, "value-key": "[SINC_WIDTH]", "command-line-flag": "-sincwidth", "description": "An integer (int or long). Full-width in voxels.", "optional": true}, {"id": "sinc_window", "name": "Sinc window", "type": "String", "value-key": "[SINC_WINDOW]", "command-line-flag": "-sincwindow", "description": "'rectangular' or 'hanning' or 'blackman'. Sinc window.", "optional": true, "value-choices": ["rectangular", "hanning", "blackman"]}, {"id": "uses_qform", "name": "Uses qform", "type": "Flag", "value-key": "[USES_QFORM]", "command-line-flag": "-usesqform", "description": "A boolean. Initialize using sform or qform.", "optional": true}, {"id": "verbose", "name": "Verbose", "type": "Number", "integer": true, "value-key": "[VERBOSE]", "command-line-flag": "-verbose", "description": "An integer (int or long). Verbose mode, 0 is least.", "optional": true}, {"id": "wm_seg", "name": "Wm seg", "type": "File", "value-key": "[WM_SEG]", "command-line-flag": "-wmseg", "description": "A file name. White matter segmentation volume needed by bbr cost function.", "optional": true}, {"id": "wmcoords", "name": "Wmcoords", "type": "File", "value-key": "[WMCOORDS]", "command-line-flag": "-wmcoords", "description": "A file name. White matter boundary coordinates for bbr cost function.", "optional": true}, {"id": "wmnorms", "name": "Wmnorms", "type": "File", "value-key": "[WMNORMS]", "command-line-flag": "-wmnorms", "description": "A file name. White matter boundary normals for bbr cost function.", "optional": true}], "outputfiles": [{"name": "Out file", "id": "out_file", "path-template": "[IN_FILE]_flirt", "path-template-stripped-extensions": [".nii.gz", ".nii"], "optional": true, "description": "An existing file name. Path/name of registered file (if generated).", "value-key": "[OUT_FILE]", "command-line-flag": "-out"}, {"name": "Out matrix file", "id": "out_matrix_file", "path-template": "[IN_FILE]_flirt.mat", "path-template-stripped-extensions": [".nii.gz", ".nii"], "optional": true, "description": "An existing file name. Path/name of calculated affine transform (if generated).", "value-key": "[OUT_MATRIX_FILE]", "command-line-flag": "-omat"}], "groups": [{"id": "mutex_group", "name": "Mutex group", "members": ["apply_xfm", "apply_isoxfm"], "mutually-exclusive": true}], "toolversion": "1.0.0", "containerimage": {"image": "glatard/fsl_6.0.4_fuzzy", "type": "docker", "index": "index.docker.io"}, "ark_id": "https://n2t.net/ark:/70798/p7ph6c7mf2kc12xf9k", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.10298359", "title": "Trainer", "description": "Tool for training machine learning models.", "publicationdate": "2023-12-08", "deprecated": false, "downloads": 18, "author": "Elodie Germani", "version": "elodiegermani/nguyen-etal-2021:latest nguyen-etal-2021:latest", "doi": "10.5281/zenodo.10298359", "schemaversion": "0.5", "container": "docker", "tags": {}, "name": "Trainer", "toolversion": "elodiegermani/nguyen-etal-2021:latest nguyen-etal-2021:latest", "commandline": "source activate neuro && export PYTHONPATH=$PYTHONPATH:/home/nguyen-etal-2021 && python3 /home/nguyen-etal-2021/code/boutiques/trainer.py [PIPELINE] [SPECIFIC] [TIMEPOINTS] [FEATURES] [ATLASES]", "containerimage": {"image": "elodiegermani/nguyen-etal-2021", "index": "docker:elodiegermani/nguyen-etal-2021:latest", "type": "docker"}, "inputs": [{"id": "pipeline", "name": "pipeline", "description": "Pre-processing pipeline", "optional": true, "type": "String", "value-key": "[PIPELINE]", "value-choices": ["reproduction_pipeline-afni_seg", "reproduction_pipeline-fsl_seg", "reproduction_pipeline-no_anat", "fmriprep_pipeline", "no_imaging_features"], "command-line-flag": "--pipeline"}, {"id": "specific", "name": "specific", "description": "Specificity of training", "optional": true, "type": "String", "value-key": "[SPECIFIC]", "command-line-flag": "--specific"}, {"id": "timepoints", "name": "timepoints", "description": "Timepoints to train", "optional": true, "type": "String", "value-key": "[TIMEPOINTS]", "command-line-flag": "--timepoints"}, {"id": "features", "name": "features", "description": "Features to train", "optional": true, "type": "String", "value-key": "[FEATURES]", "command-line-flag": "--features"}, {"id": "atlases", "name": "atlases", "description": "Atlases to train", "optional": true, "type": "String", "value-key": "[ATLASES]", "command-line-flag": "--atlases"}], "suggestedresources": {"cpu-cores": 4, "ram": 8, "walltime-estimate": 200}, "ark_id": "https://n2t.net/ark:/70798/p7kh330hg26v461jng", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.8357249", "title": "FreeSurfer-Recon-all local Gyrification Index (lGI)", "description": "Performs all, or any part of, the FreeSurfer cortical reconstruction process (https://surfer.nmr.mgh.harvard.edu/fswiki/recon-all) + LGI (https://surfer.nmr.mgh.harvard.edu/fswiki/LGI)", "publicationdate": "2023-09-16", "deprecated": false, "downloads": 17, "author": "Laboratory for Computational Neuroimaging ", "version": "unknown", "doi": "10.5281/zenodo.8357249", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "suggestedresources": {"ram": 10240, "walltime-estimate": 960, "cpu-cores": 1}, "outputfiles": [{"name": "Output", "optional": false, "description": "The subject data upon which to operate ", "id": "subjid_output", "path-template": "[SUBJID]"}], "name": "FreeSurfer-Recon-all", "containerimage": {"index": "docker://", "image": "freesurfer/freesurfer:7.1.1", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; recon-all [SUBJID] [INPUT] [DIRECTIVES] [QCACHE] [MPRAGE] [3T] [CW256] [NOTAL-CHECK] [HYPPOCAMPAL-SUBFIELDS] [BRAINSTEM-STRUCTURES] [NO-WSGCAATLAS] [NO-SKULLSTRIP] [LOCALGI]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "Output name", "command-line-flag": "-subjid", "optional": false, "value-key": "[SUBJID]", "type": "String", "id": "subjid"}, {"name": "NIFTI file", "id": "input", "optional": true, "value-key": "[INPUT]", "description": "Single NIFTI file from series.", "command-line-flag": "-i", "type": "File"}, {"name": "Directive", "default-value": "-all", "value-key": "[DIRECTIVES]", "optional": false, "type": "String", "id": "directives", "value-choices": ["-all", "-autorecon1", "-autorecon2", "-autorecon2-cp", "-autorecon2-wm", "-autorecon2-inflate1", "-autorecon2-perhemi", "-autorecon3"]}, {"name": "qcache", "id": "qcache_flag", "optional": true, "value-key": "[QCACHE]", "description": "Produce the pre-cached files required by the Qdec utility, allowing rapid analysis of group data.", "command-line-flag": "-qcache", "type": "Flag"}, {"name": "mprage", "id": "mprage_flag", "optional": true, "value-key": "[MPRAGE]", "description": "Assume scan parameters are MGH MP-RAGE protocol.", "command-line-flag": "-mprage", "type": "Flag"}, {"name": "3T", "id": "3T_flag", "optional": true, "value-key": "[3T]", "description": "The -3T flag enables two specific options in recon-all for images acquired with a 3T scanner:  3T-specific NU intensity correction parameters are used in the Non-Uniform normalization stage, and the Schwartz 3T atlas is used for Talairach alignment", "command-line-flag": "-3T", "type": "Flag"}, {"name": "cw256", "id": "cw256_flag", "optional": true, "value-key": "[CW256]", "description": "Include this flag after -autorecon1 if images have a FOV > 256.", "command-line-flag": "-cw256", "type": "Flag"}, {"name": "Notal check", "id": "notal_flag", "optional": true, "value-key": "[NOTAL-CHECK]", "description": "Skip the automatic failure detection of Talairach alignment.", "command-line-flag": "-notal-check", "type": "Flag"}, {"name": "Hippocampal-subfileds-T1", "id": "hippocampal_subfields_T1_flag", "optional": true, "value-key": "[HYPPOCAMPAL-SUBFIELDS]", "description": "Segmentation of hippocampal subfields using input T1 scan.", "command-line-flag": "-hippocampal-subfields-T1", "type": "Flag"}, {"name": "Brainstem Structures", "id": "brainstem_structures_flag", "optional": true, "value-key": "[BRAINSTEM-STRUCTURES]", "description": "Segmentation of brainstem structures.", "command-line-flag": "-brainstem-structures", "type": "Flag"}, {"name": "No wsgcaatlas", "id": "no_wsgcaatlas_flag", "optional": true, "value-key": "[NO-WSGCAATLAS]", "description": "Do not use GCA atlas when skull stripping.", "command-line-flag": "-no-wsgcaatlas", "type": "Flag"}, {"name": "No skull strip", "id": "noskullstrip_flag", "optional": true, "value-key": "[NO-SKULLSTRIP]", "description": "Exclude skull strip step.", "command-line-flag": "-noskullstrip", "type": "Flag"}, {"name": "local Gyrification Index", "id": "localGI_flag", "optional": true, "value-key": "[LOCALGI]", "description": "Perform local Gyrification Index", "command-line-flag": "-lgi", "type": "Flag"}], "custom": {"cbrain:author": "Nigel Yong <hey@nigelyong.com>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7m8p9g9q483b8s5x5", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7545769", "title": "FreeSurfer-Recon-all_v7", "description": "Performs all, or any part of, the FreeSurfer cortical reconstruction process (https://surfer.nmr.mgh.harvard.edu/fswiki/recon-all).", "publicationdate": "2023-01-17", "deprecated": false, "downloads": 17, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.3.2", "doi": "10.5281/zenodo.7545769", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "suggestedresources": {"ram": 10240, "walltime-estimate": 960, "cpu-cores": 1}, "outputfiles": [{"name": "Output", "optional": false, "description": "The subject data upon which to operate ", "id": "subjid_output", "path-template": "[SUBJID]"}], "name": "FreeSurfer-Recon-all_v7", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_7.3.2", "type": "singularity"}, "toolversion": "v7.3.2", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; recon-all [SUBJID] [INPUT] [DIRECTIVES] [QCACHE] [MPRAGE] [3T] [CW256] [NOTAL-CHECK] [HYPPOCAMPAL-SUBFIELDS] [BRAINSTEM-STRUCTURES] [NO-WSGCAATLAS] [NO-SKULLSTRIP]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "Output name", "command-line-flag": "-subjid", "optional": false, "value-key": "[SUBJID]", "type": "String", "id": "subjid"}, {"name": "NIFTI file", "id": "input", "optional": false, "value-key": "[INPUT]", "description": "Single NIFTI file from series.", "command-line-flag": "-i", "type": "File"}, {"name": "Directive", "default-value": "-all", "value-key": "[DIRECTIVES]", "optional": false, "type": "String", "id": "directives", "value-choices": ["-all", "-autorecon1", "-autorecon2", "-autorecon2-cp", "-autorecon2-wm", "-autorecon2-inflate1", "-autorecon2-perhemi", "-autorecon3"]}, {"name": "qcache", "id": "qcache_flag", "optional": true, "value-key": "[QCACHE]", "description": "Produce the pre-cached files required by the Qdec utility, allowing rapid analysis of group data.", "command-line-flag": "-qcache", "type": "Flag"}, {"name": "mprage", "id": "mprage_flag", "optional": true, "value-key": "[MPRAGE]", "description": "Assume scan parameters are MGH MP-RAGE protocol.", "command-line-flag": "-mprage", "type": "Flag"}, {"name": "3T", "id": "3T_flag", "optional": true, "value-key": "[3T]", "description": "The -3T flag enables two specific options in recon-all for images acquired with a 3T scanner:  3T-specific NU intensity correction parameters are used in the Non-Uniform normalization stage, and the Schwartz 3T atlas is used for Talairach alignment", "command-line-flag": "-3T", "type": "Flag"}, {"name": "cw256", "id": "cw256_flag", "optional": true, "value-key": "[CW256]", "description": "Include this flag after -autorecon1 if images have a FOV > 256.", "command-line-flag": "-cw256", "type": "Flag"}, {"name": "Notal check", "id": "notal_flag", "optional": true, "value-key": "[NOTAL-CHECK]", "description": "Skip the automatic failure detection of Talairach alignment.", "command-line-flag": "-notal-check", "type": "Flag"}, {"name": "Hippocampal-subfileds-T1", "id": "hippocampal_subfields_T1_flag", "optional": true, "value-key": "[HYPPOCAMPAL-SUBFIELDS]", "description": "Segmentation of hippocampal subfields using input T1 scan.", "command-line-flag": "-hippocampal-subfields-T1", "type": "Flag"}, {"name": "Brainstem Structures", "id": "brainstem_structures_flag", "optional": true, "value-key": "[BRAINSTEM-STRUCTURES]", "description": "Segmentation of brainstem structures.", "command-line-flag": "-brainstem-structures", "type": "Flag"}, {"name": "No wsgcaatlas", "id": "no_wsgcaatlas_flag", "optional": true, "value-key": "[NO-WSGCAATLAS]", "description": "Do not use GCA atlas when skull stripping.", "command-line-flag": "-no-wsgcaatlas", "type": "Flag"}, {"name": "No skull strip", "id": "noskullstrip_flag", "optional": true, "value-key": "[NO-SKULLSTRIP]", "description": "Exclude skull strip step.", "command-line-flag": "-noskullstrip", "type": "Flag"}], "ark_id": "https://n2t.net/ark:/70798/p77rxzc2s48fd8rf86", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.10308707", "title": "FLIRT 6.0.4", "description": "FSL FLIRT, as implemented in Nipype (module: nipype.interfaces.fsl, interface: FLIRT).", "publicationdate": "2023-12-08", "deprecated": false, "downloads": 17, "author": "Nipype (interface), Oxford Centre for Functional MRI of the Brain (FMRIB) (tool)", "version": "1.0.0", "doi": "10.5281/zenodo.10308707", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "fmri"], "source": "nipype-interface"}, "name": "FLIRT 6.0.4", "commandline": "flirt [ANGLE_REP] [APPLY_ISOXFM] [APPLY_XFM] [BBRSLOPE] [BBRTYPE] [BGVALUE] [BINS] [COARSE_SEARCH] [COST] [COST_FUNC] [DATATYPE] [DOF] [ECHOSPACING] [FIELDMAP] [FIELDMAPMASK] [FINE_SEARCH] [FORCE_SCALING] [IN_FILE] [IN_MATRIX_FILE] [IN_WEIGHT] [INTERP] [MIN_SAMPLING] [NO_CLAMP] [NO_RESAMPLE] [NO_RESAMPLE_BLUR] [NO_SEARCH] [PADDING_SIZE] [PEDIR] [REF_WEIGHT] [REFERENCE] [RIGID2D] [SCHEDULE] [SEARCHR_X] [SEARCHR_Y] [SEARCHR_Z] [SINC_WIDTH] [SINC_WINDOW] [USES_QFORM] [VERBOSE] [WM_SEG] [WMCOORDS] [WMNORMS] [OUT_FILE] [OUT_MATRIX_FILE]", "inputs": [{"id": "angle_rep", "name": "Angle rep", "type": "String", "value-key": "[ANGLE_REP]", "command-line-flag": "-anglerep", "description": "'quaternion' or 'euler'. Representation of rotation angles.", "optional": true, "value-choices": ["quaternion", "euler"]}, {"id": "apply_isoxfm", "name": "Apply isoxfm", "type": "Number", "value-key": "[APPLY_ISOXFM]", "command-line-flag": "-applyisoxfm", "description": "A float. As applyxfm but forces isotropic resampling.", "optional": true}, {"id": "apply_xfm", "name": "Apply xfm", "type": "Flag", "value-key": "[APPLY_XFM]", "command-line-flag": "-applyxfm", "description": "A boolean. Apply transformation supplied by in_matrix_file or uses_qform to use the affine matrix stored in the reference header.", "optional": true}, {"id": "bbrslope", "name": "Bbrslope", "type": "Number", "value-key": "[BBRSLOPE]", "command-line-flag": "-bbrslope", "description": "A float. Value of bbr slope.", "optional": true}, {"id": "bbrtype", "name": "Bbrtype", "type": "String", "value-key": "[BBRTYPE]", "command-line-flag": "-bbrtype", "description": "'signed' or 'global_abs' or 'local_abs'. Type of bbr cost function: signed [default], global_abs, local_abs.", "optional": true, "value-choices": ["signed", "global_abs", "local_abs"]}, {"id": "bgvalue", "name": "Bgvalue", "type": "Number", "value-key": "[BGVALUE]", "command-line-flag": "-setbackground", "description": "A float. Use specified background value for points outside fov.", "optional": true}, {"id": "bins", "name": "Bins", "type": "Number", "integer": true, "value-key": "[BINS]", "command-line-flag": "-bins", "description": "An integer (int or long). Number of histogram bins.", "optional": true}, {"id": "coarse_search", "name": "Coarse search", "type": "Number", "integer": true, "value-key": "[COARSE_SEARCH]", "command-line-flag": "-coarsesearch", "description": "An integer (int or long). Coarse search delta angle.", "optional": true}, {"id": "cost", "name": "Cost", "type": "String", "value-key": "[COST]", "command-line-flag": "-cost", "description": "'mutualinfo' or 'corratio' or 'normcorr' or 'normmi' or 'leastsq' or 'labeldiff' or 'bbr'. Cost function.", "optional": true, "value-choices": ["mutualinfo", "corratio", "normcorr", "normmi", "leastsq", "labeldiff", "bbr"]}, {"id": "cost_func", "name": "Cost func", "type": "String", "value-key": "[COST_FUNC]", "command-line-flag": "-searchcost", "description": "'mutualinfo' or 'corratio' or 'normcorr' or 'normmi' or 'leastsq' or 'labeldiff' or 'bbr'. Cost function.", "optional": true, "value-choices": ["mutualinfo", "corratio", "normcorr", "normmi", "leastsq", "labeldiff", "bbr"]}, {"id": "datatype", "name": "Datatype", "type": "String", "value-key": "[DATATYPE]", "command-line-flag": "-datatype", "description": "'char' or 'short' or 'int' or 'float' or 'double'. Force output data type.", "optional": true, "value-choices": ["char", "short", "int", "float", "double"]}, {"id": "dof", "name": "Dof", "type": "Number", "integer": true, "value-key": "[DOF]", "command-line-flag": "-dof", "description": "An integer (int or long). Number of transform degrees of freedom.", "optional": true}, {"id": "echospacing", "name": "Echospacing", "type": "Number", "value-key": "[ECHOSPACING]", "command-line-flag": "-echospacing", "description": "A float. Value of epi echo spacing - units of seconds.", "optional": true}, {"id": "fieldmap", "name": "Fieldmap", "type": "File", "value-key": "[FIELDMAP]", "command-line-flag": "-fieldmap", "description": "A file name. Fieldmap image in rads/s - must be already registered to the reference image.", "optional": true}, {"id": "fieldmapmask", "name": "Fieldmapmask", "type": "File", "value-key": "[FIELDMAPMASK]", "command-line-flag": "-fieldmapmask", "description": "A file name. Mask for fieldmap image.", "optional": true}, {"id": "fine_search", "name": "Fine search", "type": "Number", "integer": true, "value-key": "[FINE_SEARCH]", "command-line-flag": "-finesearch", "description": "An integer (int or long). Fine search delta angle.", "optional": true}, {"id": "force_scaling", "name": "Force scaling", "type": "Flag", "value-key": "[FORCE_SCALING]", "command-line-flag": "-forcescaling", "description": "A boolean. Force rescaling even for low-res images.", "optional": true}, {"id": "in_file", "name": "In file", "type": "File", "value-key": "[IN_FILE]", "command-line-flag": "-in", "description": "An existing file name. Input file.", "optional": false}, {"id": "in_matrix_file", "name": "In matrix file", "type": "File", "value-key": "[IN_MATRIX_FILE]", "command-line-flag": "-init", "description": "A file name. Input 4x4 affine matrix.", "optional": true}, {"id": "in_weight", "name": "In weight", "type": "File", "value-key": "[IN_WEIGHT]", "command-line-flag": "-inweight", "description": "An existing file name. File for input weighting volume.", "optional": true}, {"id": "interp", "name": "Interp", "type": "String", "value-key": "[INTERP]", "command-line-flag": "-interp", "description": "'trilinear' or 'nearestneighbour' or 'sinc' or 'spline'. Final interpolation method used in reslicing.", "optional": true, "value-choices": ["trilinear", "nearestneighbour", "sinc", "spline"]}, {"id": "min_sampling", "name": "Min sampling", "type": "Number", "value-key": "[MIN_SAMPLING]", "command-line-flag": "-minsampling", "description": "A float. Set minimum voxel dimension for sampling.", "optional": true}, {"id": "no_clamp", "name": "No clamp", "type": "Flag", "value-key": "[NO_CLAMP]", "command-line-flag": "-noclamp", "description": "A boolean. Do not use intensity clamping.", "optional": true}, {"id": "no_resample", "name": "No resample", "type": "Flag", "value-key": "[NO_RESAMPLE]", "command-line-flag": "-noresample", "description": "A boolean. Do not change input sampling.", "optional": true}, {"id": "no_resample_blur", "name": "No resample blur", "type": "Flag", "value-key": "[NO_RESAMPLE_BLUR]", "command-line-flag": "-noresampblur", "description": "A boolean. Do not use blurring on downsampling.", "optional": true}, {"id": "no_search", "name": "No search", "type": "Flag", "value-key": "[NO_SEARCH]", "command-line-flag": "-nosearch", "description": "A boolean. Set all angular searches to ranges 0 to 0.", "optional": true}, {"id": "padding_size", "name": "Padding size", "type": "Number", "integer": true, "value-key": "[PADDING_SIZE]", "command-line-flag": "-paddingsize", "description": "An integer (int or long). For applyxfm: interpolates outside image by size.", "optional": true}, {"id": "pedir", "name": "Pedir", "type": "Number", "integer": true, "value-key": "[PEDIR]", "command-line-flag": "-pedir", "description": "An integer (int or long). Phase encode direction of epi - 1/2/3=x/y/z & -1/-2/-3=-x/-y/-z.", "optional": true}, {"id": "ref_weight", "name": "Ref weight", "type": "File", "value-key": "[REF_WEIGHT]", "command-line-flag": "-refweight", "description": "An existing file name. File for reference weighting volume.", "optional": true}, {"id": "reference", "name": "Reference", "type": "File", "value-key": "[REFERENCE]", "command-line-flag": "-ref", "description": "An existing file name. Reference file.", "optional": false}, {"id": "rigid2D", "name": "Rigid2d", "type": "Flag", "value-key": "[RIGID2D]", "command-line-flag": "-2D", "description": "A boolean. Use 2d rigid body mode - ignores dof.", "optional": true}, {"id": "schedule", "name": "Schedule", "type": "File", "value-key": "[SCHEDULE]", "command-line-flag": "-schedule", "description": "An existing file name. Replaces default schedule.", "optional": true}, {"id": "searchr_x", "name": "Searchr x", "type": "Number", "list": true, "integer": true, "min-list-entries": 2, "max-list-entries": 2, "value-key": "[SEARCHR_X]", "command-line-flag": "-searchrx", "description": "A list of from 2 to 2 items which are an integer (int or long). Search angles along x-axis, in degrees.", "optional": true}, {"id": "searchr_y", "name": "Searchr y", "type": "Number", "list": true, "integer": true, "min-list-entries": 2, "max-list-entries": 2, "value-key": "[SEARCHR_Y]", "command-line-flag": "-searchry", "description": "A list of from 2 to 2 items which are an integer (int or long). Search angles along y-axis, in degrees.", "optional": true}, {"id": "searchr_z", "name": "Searchr z", "type": "Number", "list": true, "integer": true, "min-list-entries": 2, "max-list-entries": 2, "value-key": "[SEARCHR_Z]", "command-line-flag": "-searchrz", "description": "A list of from 2 to 2 items which are an integer (int or long). Search angles along z-axis, in degrees.", "optional": true}, {"id": "sinc_width", "name": "Sinc width", "type": "Number", "integer": true, "value-key": "[SINC_WIDTH]", "command-line-flag": "-sincwidth", "description": "An integer (int or long). Full-width in voxels.", "optional": true}, {"id": "sinc_window", "name": "Sinc window", "type": "String", "value-key": "[SINC_WINDOW]", "command-line-flag": "-sincwindow", "description": "'rectangular' or 'hanning' or 'blackman'. Sinc window.", "optional": true, "value-choices": ["rectangular", "hanning", "blackman"]}, {"id": "uses_qform", "name": "Uses qform", "type": "Flag", "value-key": "[USES_QFORM]", "command-line-flag": "-usesqform", "description": "A boolean. Initialize using sform or qform.", "optional": true}, {"id": "verbose", "name": "Verbose", "type": "Number", "integer": true, "value-key": "[VERBOSE]", "command-line-flag": "-verbose", "description": "An integer (int or long). Verbose mode, 0 is least.", "optional": true}, {"id": "wm_seg", "name": "Wm seg", "type": "File", "value-key": "[WM_SEG]", "command-line-flag": "-wmseg", "description": "A file name. White matter segmentation volume needed by bbr cost function.", "optional": true}, {"id": "wmcoords", "name": "Wmcoords", "type": "File", "value-key": "[WMCOORDS]", "command-line-flag": "-wmcoords", "description": "A file name. White matter boundary coordinates for bbr cost function.", "optional": true}, {"id": "wmnorms", "name": "Wmnorms", "type": "File", "value-key": "[WMNORMS]", "command-line-flag": "-wmnorms", "description": "A file name. White matter boundary normals for bbr cost function.", "optional": true}], "outputfiles": [{"name": "Out file", "id": "out_file", "path-template": "[IN_FILE]_flirt", "path-template-stripped-extensions": [".nii.gz", ".nii"], "optional": true, "description": "An existing file name. Path/name of registered file (if generated).", "value-key": "[OUT_FILE]", "command-line-flag": "-out"}, {"name": "Out matrix file", "id": "out_matrix_file", "path-template": "[IN_FILE]_flirt.mat", "path-template-stripped-extensions": [".nii.gz", ".nii"], "optional": true, "description": "An existing file name. Path/name of calculated affine transform (if generated).", "value-key": "[OUT_MATRIX_FILE]", "command-line-flag": "-omat"}], "groups": [{"id": "mutex_group", "name": "Mutex group", "members": ["apply_xfm", "apply_isoxfm"], "mutually-exclusive": true}], "toolversion": "1.0.0", "containerimage": {"image": "vnmd/fsl_6.0.4", "type": "docker", "index": "index.docker.io"}, "ark_id": "https://n2t.net/ark:/70798/p74c6c66n51v499x4g", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.8250478", "title": "Brainstorm Tool", "description": "Enables to perform the pre-processing steps on EEG data.", "publicationdate": "2023-03-08", "deprecated": false, "downloads": 17, "author": "Brainstorm team <https://neuroimage.usc.edu/brainstorm/AboutUs>", "version": "v1.0", "doi": "https://zenodo.org/record/8250478", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "Brainstorm", "toolversion": "v1.0", "commandline": "bash /Brainstorm/Brainstorm-Tool/compiled_tool/run_bst_tool.sh /usr/local/MATLAB/MATLAB_Runtime/v910/ [BIDS_DATASET] [PIPELINE]", "containerimage": {"image": "corentinlabelle/brainstorm-tool-test", "index": "docker://", "type": "singularity"}, "inputs": [{"id": "bids_dataset", "name": "BIDS dataset", "optional": false, "type": "File", "description": "EEG BIDS dataset", "value-key": "[BIDS_DATASET]"}, {"id": "pipeline", "name": "Pipeline", "optional": false, "type": "File", "description": "Pipeline", "value-key": "[PIPELINE]"}], "outputfiles": [{"id": "output_directory", "name": "Output Directory", "optional": false, "description": "Output directory", "path-template": "[BIDS_DATASET]_output"}], "suggestedresources": {"walltime-estimate": 10800, "ram": 8}, "custom": {"cbrain:author": "Corentin Labelle <corentin.labelle.1@ulaval.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7qv56zp34rr96b031", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7988259", "title": "mincreshape", "description": "mincreshape - cuts a hyperslab out of a minc file (with dimension re-ordering)", "publicationdate": "2023-05-31", "deprecated": false, "downloads": 16, "author": "Peter Neelin", "version": "2.3.01", "doi": "10.5281/zenodo.7988259", "schemaversion": "0.5", "container": "docker", "tags": {"domain": "neuroimaging"}, "name": "mincreshape", "toolversion": "2.3.01", "commandline": "source /etc/profile ; mincreshape [DIMSIZE] [-XDIRECTION] [-YDIRECTION] [-ZDIRECTION] [DIMORDER] [INFILE] [OUTFILE]", "containerimage": {"image": "simexp/minc-toolkit", "index": "docker://", "type": "docker"}, "shell": "/bin/bash", "inputs": [{"id": "infile", "name": "Input file", "optional": false, "description": "File to reshape", "type": "File", "value-key": "[INFILE]"}, {"id": "outfile_name", "name": "Output file name", "optional": false, "description": "Name of reshaped file", "type": "String", "value-key": "[OUTFILE]"}, {"id": "flip_xdirection", "name": "-xdirection", "optional": true, "description": "Flip images to give negative xspace:step value (right-to-left).", "type": "Flag", "command-line-flag": "-xdirection", "value-key": "[-XDIRECTION]"}, {"id": "flip_ydirection", "name": "-ydirection", "optional": true, "description": "Flip images to give negative yspace:step value (ant-to-post).", "type": "Flag", "command-line-flag": "-ydirection", "value-key": "[-YDIRECTION]"}, {"id": "flip_zdirection", "name": "-zdirection", "optional": true, "description": "Flip images to give negative zspace:step value (sup-to-inf).", "type": "Flag", "command-line-flag": "-zdirection", "value-key": "[-ZDIRECTION]"}, {"id": "dimorder", "name": "dimorder", "optional": true, "description": "Specify dimension order (<dim1>,<dim2>,<dim3>,...).", "type": "String", "command-line-flag": "-dimorder", "value-key": "[DIMORDER]"}, {"id": "dimsize", "name": "dimsize", "optional": true, "description": "Specify the size of a named dimension (<dimension>=<size>).", "type": "String", "command-line-flag": "-dimsize", "value-key": "[DIMSIZE]"}], "outputfiles": [{"id": "outfile", "name": "Output file", "optional": false, "path-template": "[OUTFILE]"}], "suggestedresources": {"cpu-cores": 1, "walltime-estimate": 60}, "ark_id": "https://n2t.net/ark:/70798/p7v6v1gzv3dp82djzj", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7542266", "title": "FreeSurfer-Recon-all_v6", "description": "Performs all, or any part of, the FreeSurfer cortical reconstruction process (https://surfer.nmr.mgh.harvard.edu/fswiki/recon-all).", "publicationdate": "2023-01-16", "deprecated": false, "downloads": 15, "author": "Laboratory for Computational Neuroimaging ", "version": "v6.0.1", "doi": "10.5281/zenodo.7542266", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "suggestedresources": {"ram": 10240, "walltime-estimate": 960, "cpu-cores": 1}, "outputfiles": [{"name": "Output", "optional": false, "description": "The subject data upon which to operate ", "id": "subjid_output", "path-template": "[SUBJID]"}], "name": "FreeSurfer-Recon-all_v6", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_6.0.1", "type": "singularity"}, "toolversion": "v6.0.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; recon-all [SUBJID] [INPUT] [DIRECTIVES] [QCACHE] [MPRAGE] [3T] [CW256] [NOTAL-CHECK] [HYPPOCAMPAL-SUBFIELDS] [BRAINSTEM-STRUCTURES] [NO-WSGCAATLAS] [NO-SKULLSTRIP]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "Output name", "command-line-flag": "-subjid", "optional": false, "value-key": "[SUBJID]", "type": "String", "id": "subjid"}, {"name": "NIFTI file", "id": "input", "optional": false, "value-key": "[INPUT]", "description": "Single NIFTI file from series.", "command-line-flag": "-i", "type": "File"}, {"name": "Directive", "default-value": "-all", "value-key": "[DIRECTIVES]", "optional": false, "type": "String", "id": "directives", "value-choices": ["-all", "-autorecon1", "-autorecon2", "-autorecon2-cp", "-autorecon2-wm", "-autorecon2-inflate1", "-autorecon2-perhemi", "-autorecon3"]}, {"name": "qcache", "id": "qcache_flag", "optional": true, "value-key": "[QCACHE]", "description": "Produce the pre-cached files required by the Qdec utility, allowing rapid analysis of group data.", "command-line-flag": "-qcache", "type": "Flag"}, {"name": "mprage", "id": "mprage_flag", "optional": true, "value-key": "[MPRAGE]", "description": "Assume scan parameters are MGH MP-RAGE protocol.", "command-line-flag": "-mprage", "type": "Flag"}, {"name": "3T", "id": "3T_flag", "optional": true, "value-key": "[3T]", "description": "The -3T flag enables two specific options in recon-all for images acquired with a 3T scanner:  3T-specific NU intensity correction parameters are used in the Non-Uniform normalization stage, and the Schwartz 3T atlas is used for Talairach alignment", "command-line-flag": "-3T", "type": "Flag"}, {"name": "cw256", "id": "cw256_flag", "optional": true, "value-key": "[CW256]", "description": "Include this flag after -autorecon1 if images have a FOV > 256.", "command-line-flag": "-cw256", "type": "Flag"}, {"name": "Notal check", "id": "notal_flag", "optional": true, "value-key": "[NOTAL-CHECK]", "description": "Skip the automatic failure detection of Talairach alignment.", "command-line-flag": "-notal-check", "type": "Flag"}, {"name": "Hippocampal-subfileds-T1", "id": "hippocampal_subfields_T1_flag", "optional": true, "value-key": "[HYPPOCAMPAL-SUBFIELDS]", "description": "Segmentation of hippocampal subfields using input T1 scan.", "command-line-flag": "-hippocampal-subfields-T1", "type": "Flag"}, {"name": "Brainstem Structures", "id": "brainstem_structures_flag", "optional": true, "value-key": "[BRAINSTEM-STRUCTURES]", "description": "Segmentation of brainstem structures.", "command-line-flag": "-brainstem-structures", "type": "Flag"}, {"name": "No wsgcaatlas", "id": "no_wsgcaatlas_flag", "optional": true, "value-key": "[NO-WSGCAATLAS]", "description": "Do not use GCA atlas when skull stripping.", "command-line-flag": "-no-wsgcaatlas", "type": "Flag"}, {"name": "No skull strip", "id": "noskullstrip_flag", "optional": true, "value-key": "[NO-SKULLSTRIP]", "description": "Exclude skull strip step.", "command-line-flag": "-noskullstrip", "type": "Flag"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7kzcn20f9f4q8d222", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.8033560", "title": "FreeSurfer-Stats2table", "description": "Converts a stats file created by recon-all into a table in which each line is a subject and each column is a parcellation (command: aparcstats2table) or segmentation (command: asegstats2table): https://surfer.nmr.mgh.harvard.edu/fswiki/aparcstats2table, https://surfer.nmr.mgh.harvard.edu/fswiki/asegstats2table.", "publicationdate": "2023-06-13", "deprecated": false, "downloads": 15, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.1.1", "doi": "10.5281/zenodo.8033560", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "outputfiles": [{"name": "Outfile", "optional": false, "description": "Output stats file", "id": "outfile", "path-template": "[STATS_FILE].csv"}], "name": "FreeSurfer-Stats2table", "containerimage": {"index": "docker://", "image": "freesurfer/freesurfer:7.1.1", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "export SUBJECTS_DIR=`pwd`/[INPUTDIR]; export FS_LICENSE=`pwd`/[LICENSE_FILE]; [STATS_COMMAND] [SUBJECTS_LIST] [HEMI] [MEAS] [STATS_FILE]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "Input directory", "optional": false, "description": "Path from working directory to subject folders.", "value-key": "[INPUTDIR]", "id": "inputdir", "type": "String"}, {"name": "License file", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "value-key": "[LICENSE_FILE]", "id": "license", "type": "File"}, {"name": "Stats Command", "optional": false, "description": "Command for the type of stats required. Either asegstats2table or aparcstats2table", "value-key": "[STATS_COMMAND]", "id": "stats_command", "type": "String"}, {"name": "Subjects list", "optional": false, "description": "List of the subjects, i.e., the subject folder names (BOB JOHN JANE ...).", "value-key": "[SUBJECTS_LIST]", "type": "String", "command-line-flag": "--subjects", "id": "subjects_list"}, {"name": "measure", "optional": true, "description": "Default: area (options: alt volume, thickness, thicknessstd, meancurv, gauscurv, foldind, curvind). Optional for aparcstats2table and asegstats2table.", "value-key": "[MEAS]", "type": "String", "command-line-flag": "--meas", "id": "meas"}, {"name": "hemisphere", "optional": true, "description": "Required for aparcstats2table - values are lh or rh. Not used for asegstats2table.", "value-key": "[HEMI]", "type": "String", "command-line-flag": "--hemi", "id": "hemi"}, {"name": "Stats file", "optional": false, "description": "Used to define the output file name. The .csv extension will be applied.", "value-key": "[STATS_FILE]", "type": "String", "command-line-flag": "--tablefile", "id": "stats_file"}], "ark_id": "https://n2t.net/ark:/70798/p7dwvm64n0r096rcbj", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7884255", "title": "FreeSurfer5-Recon-all-qcache", "description": "resample longitudinal data onto the average subject (called fsaverage) & smooth it at a range of FWHM: (https://surfer.nmr.mgh.harvard.edu/fswiki/qcache).", "publicationdate": "2023-05-01", "deprecated": false, "downloads": 14, "author": "Laboratory for Computational Neuroimaging ", "version": "v5.3", "doi": "10.5281/zenodo.7884255", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer5-Recon-all-qcache", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_5.3", "type": "singularity"}, "toolversion": "v5.3", "commandline": "export SUBJECTS_DIR=`pwd`; recon-all -long [TP] [BASE] -qcache", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "timepoint", "id": "tp", "optional": false, "value-key": "[TP]", "description": "input timepoint", "type": "String"}, {"name": "base template", "id": "base", "optional": false, "value-key": "[BASE]", "description": "subject template", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p780qw3jq4rt565q9k", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.10298335", "title": "Image processing", "description": "Tool for image processing workflows.", "publicationdate": "2023-12-08", "deprecated": false, "downloads": 14, "author": "Elodie Germani", "version": "elodiegermani/nguyen-etal-2021:latest nguyen-etal-2021:latest", "doi": "10.5281/zenodo.10298335", "schemaversion": "0.5", "container": "docker", "tags": {}, "name": "Image processing", "toolversion": "elodiegermani/nguyen-etal-2021:latest nguyen-etal-2021:latest", "commandline": "source activate neuro && export PYTHONPATH=$PYTHONPATH:/home/nguyen-etal-2021 && python3 /home/nguyen-etal-2021/code/boutiques/image_processing.py [PIPELINE] [STEP] [BASE_DIR] [SUBJECT_LIST]", "containerimage": {"image": "elodiegermani/nguyen-etal-2021", "index": "docker:elodiegermani/nguyen-etal-2021:latest", "type": "docker"}, "inputs": [{"id": "pipeline", "name": "pipeline", "description": "Pre-processing pipeline", "optional": true, "type": "String", "value-key": "[PIPELINE]", "value-choices": ["reproduction_pipeline-afni_seg", "reproduction_pipeline-fsl_seg", "reproduction_pipeline-no_anat"], "command-line-flag": "--pipeline"}, {"id": "step", "name": "step", "description": "Which step to run", "optional": true, "type": "String", "value-key": "[STEP]", "value-choices": ["func", "anat", "ica", "confound", "feature"], "command-line-flag": "--step"}, {"id": "base_dir", "name": "base_dir", "description": "Absolute path to this directory", "optional": true, "type": "String", "value-key": "[BASE_DIR]", "command-line-flag": "--base_dir"}, {"id": "subject_list", "name": "subject_list", "description": "Subject list", "optional": true, "type": "String", "value-key": "[SUBJECT_LIST]", "command-line-flag": "--subject_list"}], "suggestedresources": {"cpu-cores": 4, "ram": 8, "walltime-estimate": 200}, "ark_id": "https://n2t.net/ark:/70798/p7g3tzhbf0xxs67hdf", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.8052752", "title": "FreeSurfer-7_1_1-Brainstem-Structures", "description": "Generates automated segmentation of four brainstem structures from T1 scan - for v7. https://surfer.nmr.mgh.harvard.edu/fswiki/BrainstemSubstructures", "publicationdate": "2023-06-18", "deprecated": false, "downloads": 13, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.1.1", "doi": "10.5281/zenodo.8052752", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer-7_1_1-Brainstem-Structures", "containerimage": {"index": "docker://", "image": "freesurfer/freesurfer:7.1.1", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "export FS_LICENSE=`pwd`/[LICENSE_FILE]; segmentBS.sh [SUBJ] [SUBJ_DIR]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "value-key": "[LICENSE_FILE]", "id": "license", "type": "File"}, {"name": "Subjects directory", "optional": true, "description": "Optional: Can override FreeSurfer subject directory.", "value-key": "[SUBJ_DIR]", "id": "subjdir", "type": "String"}, {"name": "Subject", "optional": false, "description": "Subject. Must have already been processed with recon-all.", "value-key": "[SUBJ]", "id": "subj", "type": "String"}], "ark_id": "https://n2t.net/ark:/70798/p7m67kpsc5s0r4x0c4", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.10305645", "title": "fsl_first_6.0.4", "description": "FIRST is a model-based segmentation and registration tool, based on a Bayesian model of shape and appearance for subcortical structures.", "publicationdate": "2023-12-08", "deprecated": false, "downloads": 13, "author": "Oxford Centre for Functional MRI of the Brain (FMRIB)", "version": "6.0.4", "doi": "10.5281/zenodo.10305645", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "mri"]}, "toolversion": "6.0.4", "name": "fsl_first_6.0.4", "descriptorurl": "https://github.com/aces/cbrain-plugins-neuro/blob/master/cbrain_task_descriptors/fsl_first.json", "commandline": "mkdir -p [OUTPUT_DIR]; run_first_all [METHOD] [BRAIN_EXTRACTED] [SPECIFIED_STRUCTURE] [AFFINE] [THREE_STAGE] [VERBOSE] [INPUT_FILE] -o [OUTPUT_DIR]/[PREFIX]", "containerimage": {"image": "vnmd/fsl_6.0.4", "index": "index.docker.io", "type": "docker"}, "inputs": [{"command-line-flag": "-m", "description": "Method must be one of 'auto' (default), 'fast', 'none', or it can be a numerical threshold value. This specifies the boundary correction method. Auto chooses different options for different structures using the settings that were found to be empirically optimal for each structure. Other options use: fast (using FAST-based, mixture-model, tissue-type classification) or threshold (thresholds a simple single-Gaussian intensity model).", "value-key": "[METHOD]", "type": "String", "list": false, "optional": true, "id": "method", "name": "Method"}, {"command-line-flag": "-i", "description": "Input image file (e.g. img.nii.gz).", "value-key": "[INPUT_FILE]", "type": "File", "list": false, "optional": false, "id": "input_file", "name": "Input file"}, {"command-line-flag": "-b", "description": "Whether the input is already brain extracted.", "value-key": "[BRAIN_EXTRACTED]", "type": "Flag", "list": false, "optional": true, "id": "brain_extracted", "name": "Brain extracted"}, {"command-line-flag": "-s", "description": "Run only on one specified structure (e.g. L_Hipp) or a comma-separated list (no spaces). Choose from: 'L_Hipp', 'R_Hipp', 'L_Accu', 'R_Accu', 'L_Amyg', 'R_Amyg', 'L_Caud', 'R_Caud', 'L_Pall', 'R_Pall', 'L_Puta', 'R_Puta', 'L_Thal', 'R_Thal', 'BrStem'.", "value-key": "[SPECIFIED_STRUCTURE]", "type": "String", "list": false, "optional": true, "id": "specified_structure", "name": "Specify structure"}, {"command-line-flag": "-a", "description": "Use affine matrix (i.e. do not re-run registration).", "value-key": "[AFFINE]", "type": "File", "list": false, "optional": true, "id": "affine", "name": "Use Affine Matrix"}, {"command-line-flag": "-3", "description": "Use 3-stage affine registration. Only currently implemented for the hippocampus.", "value-key": "[THREE_STAGE]", "type": "Flag", "list": false, "optional": true, "id": "three_stage", "name": "Three stage registration"}, {"command-line-flag": "-v", "description": "Verbose output.", "value-key": "[VERBOSE]", "type": "Flag", "list": false, "optional": true, "id": "verbose", "name": "Verbose"}, {"description": "Prefix for each files in the directory output.", "value-key": "[PREFIX]", "type": "String", "optional": false, "list": false, "default-value": "output", "id": "prefix", "name": "Prefix"}], "outputfiles": [{"id": "outputs", "name": "First Outputs", "description": "Output directory of First", "value-key": "[OUTPUT_DIR]", "path-template": "[INPUT_FILE]", "list": false, "path-template-stripped-extensions": [".nii.gz", ".nii"]}, {"id": "std_sub_outputs", "name": "Registered outputs", "description": "Std sub output", "path-template": "[INPUT_FILE]_to_std_sub*", "list": true, "path-template-stripped-extensions": [".nii.gz", ".nii"]}], "tests": [{"name": "fsl_first_test", "invocation": {"input_file": "sub-01_T1w.nii.gz", "prefix": "img_first"}, "assertions": {"exit-code": 0, "output-files": [{"id": "outputs"}]}}], "ark_id": "https://n2t.net/ark:/70798/p7fjd00hp67k208m5q", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7470208", "title": "FreeSurfer-freeview", "description": "Save screenshot using freeview to file.", "publicationdate": "2022-12-21", "deprecated": false, "downloads": 13, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.1.1", "doi": "10.5281/zenodo.7470208", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer-freeview", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_7.1.10", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "(Xvfb :99 -nolisten tcp -nolisten unix & export DISPLAY=:99) && (export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; freeview -f [FILE] -viewport [VIEW] -colorscale -ss [OUTNAME] 1 autotrim)", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "image file", "id": "imgfile", "optional": false, "value-key": "[FILE]", "description": "file", "type": "String"}, {"name": "view", "id": "view", "optional": false, "value-key": "[VIEW]", "description": "view", "type": "String", "value-choices": ["3D", "sagittal", "coronal", "axial"]}, {"name": "output file name", "id": "outname", "optional": false, "value-key": "[OUTNAME]", "description": "outname", "type": "String"}], "outputfiles": [{"id": "outfile", "name": "output file", "optional": false, "path-template": "[OUTNAME]"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7xmcp7mw4z1m61zch", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7868966", "title": "FreeSurfer5-Recon-all-base", "description": "create an unbiased template from all time points for each subject and process it with recon-all -base: (https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalProcessing).", "publicationdate": "2023-04-26", "deprecated": false, "downloads": 12, "author": "Laboratory for Computational Neuroimaging ", "version": "v5.3", "doi": "10.5281/zenodo.7868966", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "outputfiles": [{"name": "Output", "optional": false, "description": "output directory", "id": "output", "path-template": "[OUTPUTDIR]"}], "name": "FreeSurfer5-Recon-all-base", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_5.3", "type": "singularity"}, "toolversion": "v5.3", "commandline": "export SUBJECTS_DIR=`pwd`; recon-all -base [OUTPUTDIR] -tp [TP1] -tp [TP2] -all", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "Output name", "optional": false, "value-key": "[OUTPUTDIR]", "type": "String", "id": "outputdir"}, {"name": "timepoint_1", "optional": false, "value-key": "[TP1]", "description": "Input directory timepoint 1", "type": "String", "id": "tp1"}, {"name": "timepoint_2", "optional": false, "value-key": "[TP2]", "description": "Input directory timepoint 2", "type": "String", "id": "tp2"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p72m9dgzf86gc15qwr", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7659044", "title": "SPM batch", "description": "Run a batch with SPM12", "publicationdate": "2023-02-20", "deprecated": false, "downloads": 12, "author": "Tristan Glatard", "version": "r7771", "doi": "10.5281/zenodo.7659044", "schemaversion": "0.5", "container": "docker", "tags": {"domain": "neuroimaging", "toolbox": "SPM"}, "name": "SPM batch", "toolversion": "r7771", "commandline": "(Xvfb :99 -nolisten tcp -nolisten unix & export DISPLAY=:99) && (cd /spm12-r7771 && octave -W [SPM_BATCH_FILE] &>[LOG_FILE])", "containerimage": {"image": "mathdugre/spm:octave", "index": "docker://", "type": "docker"}, "inputs": [{"id": "spm_batch_file", "name": "SPM batch file", "type": "File", "value-key": "[SPM_BATCH_FILE]"}, {"id": "log_file_name", "name": "Name of output log file (stdout & stderr)", "optional": true, "default-value": "batch.log", "type": "String", "value-key": "[LOG_FILE]"}], "outputfiles": [{"id": "log_file", "name": "Log file (stdout & stderr)", "optional": false, "path-template": "[LOG_FILE]"}], "ark_id": "https://n2t.net/ark:/70798/p7w2r51w6286v8t332", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7900708", "title": "FreeSurfer6-Recon-all-qcache", "description": "resample longitudinal data onto the average subject (called fsaverage) & smooth it at a range of FWHM: (https://surfer.nmr.mgh.harvard.edu/fswiki/qcache).", "publicationdate": "2023-05-05", "deprecated": false, "downloads": 11, "author": "Laboratory for Computational Neuroimaging ", "version": "v6.0.1", "doi": "10.5281/zenodo.7900708", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer6-Recon-all-qcache", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_6.0.1", "type": "singularity"}, "toolversion": "v6.0.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; recon-all -long [TP] [BASE] -qcache", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "timepoint", "id": "tp", "optional": false, "value-key": "[TP]", "description": "input timepoint", "type": "String"}, {"name": "base template", "id": "base", "optional": false, "value-key": "[BASE]", "description": "subject template", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7rxfjzw42pz92f02p", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.14070498", "title": "Brainstorm", "description": "Enables to perform the pre-processing steps on EEG data.", "publicationdate": "2024-11-11", "deprecated": false, "downloads": 11, "author": "Brainstorm team <https://neuroimage.usc.edu/brainstorm/AboutUs>", "version": "v1.0.4", "doi": "10.5281/zenodo.14070498", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["brainstorm", "eeg", "eegnet"]}, "name": "Brainstorm", "toolversion": "v1.0.4", "commandline": "bash /Brainstorm/Brainstorm-Tool/src/run_bst_tool.sh /usr/local/MATLAB/MATLAB_Runtime/v910/ [BIDS_DATASET] [PIPELINE] [ADDITIONAL_FILES]", "containerimage": {"image": "corentinlabelle/brainstorm-tool:v1.0.4", "index": "docker://", "type": "singularity"}, "inputs": [{"id": "bids_dataset", "name": "BIDS dataset", "optional": false, "type": "File", "description": "EEG BIDS dataset", "value-key": "[BIDS_DATASET]"}, {"id": "pipeline", "name": "Pipeline", "optional": false, "type": "File", "description": "Pipeline", "value-key": "[PIPELINE]"}, {"id": "additional_files", "name": "Additional Files", "optional": true, "type": "File", "description": "Folder with files needed for the analysis", "value-key": "[ADDITIONAL_FILES]"}], "outputfiles": [{"id": "output_directory", "name": "Output Directory", "optional": false, "description": "Output directory", "path-template": "[BIDS_DATASET]_output"}], "suggestedresources": {"walltime-estimate": 36000, "ram": 8}, "custom": {"cbrain:author": "Corentin Labelle <corentin.labelle.1@ulaval.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7v1wxk4p19bj0fhgs", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7893729", "title": "FreeSurfer5-mris_preproc", "description": "Concatenate surface-based data with mris_preproc (https://surfer.nmr.mgh.harvard.edu/fswiki/mris_preproc).", "publicationdate": "2023-05-03", "deprecated": false, "downloads": 11, "author": "Laboratory for Computational Neuroimaging ", "version": "v5.3", "doi": "10.5281/zenodo.7893729", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer5-mris_preproc", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_5.3", "type": "singularity"}, "toolversion": "v5.3", "commandline": "export SUBJECTS_DIR=`pwd`; mris_preproc --fsgd [FSGD] --cache-in [CACHEIN] --target [TARGET] --hemi [HEMI] --out [OUT]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "fsgd", "id": "fsgd", "optional": false, "value-key": "[FSGD]", "description": "fsgd file", "type": "String"}, {"name": "cache-in", "id": "cachein", "optional": false, "value-key": "[CACHEIN]", "description": "cache-in", "type": "String"}, {"name": "target", "id": "target", "optional": false, "value-key": "[TARGET]", "description": "target", "type": "String"}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}, {"name": "out", "id": "out", "optional": false, "value-key": "[OUT]", "description": "output directory", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p78f1c7h047h16t8c6", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7920876", "title": "FreeSurfer7-Recon-all-qcache", "description": "resample longitudinal data onto the average subject (called fsaverage) & smooth it at a range of FWHM: (https://surfer.nmr.mgh.harvard.edu/fswiki/qcache).", "publicationdate": "2023-05-10", "deprecated": false, "downloads": 11, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.3.2", "doi": "10.5281/zenodo.7920876", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer7-Recon-all-qcache", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_7.3.2", "type": "singularity"}, "toolversion": "v7.3.2", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; recon-all -long [TP] [BASE] -qcache", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "timepoint", "id": "tp", "optional": false, "value-key": "[TP]", "description": "input timepoint", "type": "String"}, {"name": "base template", "id": "base", "optional": false, "value-key": "[BASE]", "description": "subject template", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7mtrnm8x83zc48q4q", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7411854", "title": "FreeSurfer-mri_glmfit_1con", "description": "Performs general linear model (GLM) analysis in the volume or the surface (https://surfer.nmr.mgh.harvard.edu/fswiki/mri_glmfit).", "publicationdate": "2022-12-07", "deprecated": false, "downloads": 11, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.1.1", "doi": "10.5281/zenodo.7411854", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer-mri_glmfit_1con", "containerimage": {"index": "docker://", "image": "freesurfer/freesurfer:7.1.1", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; mri_glmfit --fsgd [FSGD] --glmdir [DIR] --y [INPUT] --surf fsaverage [HEMI] --C [CON]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "fsgd", "id": "fsgd", "optional": false, "value-key": "[FSGD]", "description": "fsgd file", "type": "String"}, {"name": "output_dir", "id": "outdir", "optional": false, "value-key": "[DIR]", "description": "output directory", "type": "String"}, {"name": "input", "id": "inputdata", "optional": false, "value-key": "[INPUT]", "description": "input file", "type": "String"}, {"name": "contrast", "id": "con", "optional": false, "value-key": "[CON]", "description": "please specify contrast", "type": "String"}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7nrm44m17dwr8spn5", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7478047", "title": "FreeSurfer-freeview", "description": "Save screenshot using freeview to file.", "publicationdate": "2022-12-23", "deprecated": false, "downloads": 11, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.1.1", "doi": "10.5281/zenodo.7478047", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "outputfiles": [{"id": "outfile", "name": "output file", "optional": false, "path-template": "[OUTNAME]"}], "name": "FreeSurfer-freeview", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_7.1.10", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "(Xvfb :99 -nolisten tcp -nolisten unix &) && (export DISPLAY=:99; export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; freeview -f [FILE] -viewport [VIEW] -colorscale -ss [OUTNAME] 1 autotrim)", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "image file", "id": "imgfile", "optional": false, "value-key": "[FILE]", "description": "file", "type": "String"}, {"name": "view", "id": "view", "optional": false, "value-key": "[VIEW]", "description": "view", "type": "String", "value-choices": ["3D", "sagittal", "coronal", "axial"]}, {"name": "output file name", "id": "outname", "optional": false, "value-key": "[OUTNAME]", "description": "outname", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7mrwxs953jh64sv3t", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7916240", "title": "FreeSurfer7-Recon-all-base", "description": "create an unbiased template from all time points for each subject and process it with recon-all -base: (https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalProcessing).", "publicationdate": "2023-05-09", "deprecated": false, "downloads": 11, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.3.2", "doi": "10.5281/zenodo.7916240", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "outputfiles": [{"name": "Output", "optional": false, "description": "output directory", "id": "output", "path-template": "[OUTPUTDIR]"}], "name": "FreeSurfer7-Recon-all-base", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_7.3.2", "type": "singularity"}, "toolversion": "v7.3.2", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; recon-all -base [OUTPUTDIR] -tp [TP1] -tp [TP2] -all", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "Output name", "optional": false, "value-key": "[OUTPUTDIR]", "type": "String", "id": "outputdir"}, {"name": "timepoint_1", "optional": false, "value-key": "[TP1]", "description": "Input directory timepoint 1", "type": "String", "id": "tp1"}, {"name": "timepoint_2", "optional": false, "value-key": "[TP2]", "description": "Input directory timepoint 2", "type": "String", "id": "tp2"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p786r7zk56c6k4qh0f", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7900706", "title": "FreeSurfer6-Recon-all-long", "description": "-long longitudinally process all timepoints with recon-all -long: (https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalProcessing).", "publicationdate": "2023-05-05", "deprecated": false, "downloads": 10, "author": "Laboratory for Computational Neuroimaging ", "version": "v6.0.1", "doi": "10.5281/zenodo.7900706", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer6-Recon-all-long", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_6.0.1", "type": "singularity"}, "toolversion": "v6.0.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; recon-all -long [TP] [BASE] -all", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "timepoint", "id": "tp", "optional": false, "value-key": "[TP]", "description": "input timepoint", "type": "String"}, {"name": "base template", "id": "base", "optional": false, "value-key": "[BASE]", "description": "subject template", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7twsjf2b9gcb0fbhh", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7900742", "title": "FreeSurfer6-long_mris_slopes", "description": "Prepare the data with long_mris_slopes for longitudinal two stage model (https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalTwoStageModel).", "publicationdate": "2023-05-05", "deprecated": false, "downloads": 10, "author": "Laboratory for Computational Neuroimaging ", "version": "v6.0.1", "doi": "10.5281/zenodo.7900742", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer6-long_mris_slopes", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_6.0.1", "type": "singularity"}, "toolversion": "v6.0.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; long_mris_slopes --qdec [QDEC] --meas [MEASURE] --hemi [HEMI] --do-avg --do-rate --do-pc1 --do-pc1fit --do-spc --do-stack --do-label --time [TIME] --qcache fsaverage --sd $SUBJECTS_DIR --stack-avg [SAVG] --stack-rate [SRATE] --stack-pc1fit [SPC1FIT] --stack-pc1 [SPC1] --stack-spc [SSPC]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "qdec table", "id": "qdec", "optional": false, "value-key": "[QDEC]", "description": "qdec table", "type": "String"}, {"name": "measure", "id": "meas", "optional": false, "value-key": "[MEASURE]", "description": "measure", "type": "String", "value-choices": ["thickness", "volume"]}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}, {"name": "time", "id": "time", "optional": false, "value-key": "[TIME]", "description": "time variable in qdec table", "type": "String"}, {"name": "stack_avg", "id": "stack_avg", "optional": false, "value-key": "[SAVG]", "description": "Output stacked avg maps on <qtarget> for all fwhm levels", "type": "String"}, {"name": "stack_rate", "id": "stack_rate", "optional": false, "value-key": "[SRATE]", "description": "Output stacked rate maps on <qtarget> for all fwhm levels", "type": "String"}, {"name": "stack_pc1fit", "id": "stack_pc1fit", "optional": false, "value-key": "[SPC1FIT]", "description": "Output stacked pc1fit maps on <qtarget> for all fwhm levels", "type": "String"}, {"name": "stack_pc1", "id": "stack_pc1", "optional": false, "value-key": "[SPC1]", "description": "Output stacked pc1 maps on <qtarget> for all fwhm levels", "type": "String"}, {"name": "stack_spc", "id": "stack_spc", "optional": false, "value-key": "[SSPC]", "description": "Output stacked spc maps on <qtarget> for all fwhm levels", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7bgr1j3k2fsc07vmz", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7972313", "title": "nii2mnc", "description": "nii2mnc: Convert NIfTI-1 files to MINC format", "publicationdate": "2023-05-26", "deprecated": false, "downloads": 10, "author": "Robert Vincent", "version": "2.3.01", "doi": "10.5281/zenodo.7972313", "schemaversion": "0.5", "container": "docker", "tags": {"domain": "neuroimaing"}, "name": "nii2mnc", "toolversion": "2.3.01", "commandline": "source /etc/profile ; nii2mnc [NII_FILE] [MINC_FILE]", "containerimage": {"image": "simexp/minc-toolkit", "index": "docker://", "type": "docker"}, "shell": "/bin/bash", "inputs": [{"id": "nii_file", "name": "NIfTI file", "optional": false, "type": "File", "value-key": "[NII_FILE]"}, {"id": "mnc_file_name", "name": "MINC file name", "optional": false, "type": "String", "value-key": "[MINC_FILE]"}], "outputfiles": [{"id": "mnc_file", "name": "MINC file", "optional": false, "path-template": "[MINC_FILE]"}], "suggestedresources": {"cpu-cores": 1, "walltime-estimate": 60}, "ark_id": "https://n2t.net/ark:/70798/p71hs7sch1qs2738b8", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7920880", "title": "FreeSurfer7-long_mris_slopes", "description": "Prepare the data with long_mris_slopes for longitudinal two stage model (https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalTwoStageModel).", "publicationdate": "2023-05-10", "deprecated": false, "downloads": 10, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.3.2", "doi": "10.5281/zenodo.7920880", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer7-long_mris_slopes", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_7.3.2", "type": "singularity"}, "toolversion": "v7.3.2", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; long_mris_slopes --qdec [QDEC] --meas [MEASURE] --hemi [HEMI] --do-avg --do-rate --do-pc1 --do-pc1fit --do-spc --do-stack --do-label --time [TIME] --qcache fsaverage --sd $SUBJECTS_DIR --stack-avg [SAVG] --stack-rate [SRATE] --stack-pc1fit [SPC1FIT] --stack-pc1 [SPC1] --stack-spc [SSPC]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "qdec table", "id": "qdec", "optional": false, "value-key": "[QDEC]", "description": "qdec table", "type": "String"}, {"name": "measure", "id": "meas", "optional": false, "value-key": "[MEASURE]", "description": "measure", "type": "String", "value-choices": ["thickness", "volume"]}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}, {"name": "time", "id": "time", "optional": false, "value-key": "[TIME]", "description": "time variable in qdec table", "type": "String"}, {"name": "stack_avg", "id": "stack_avg", "optional": false, "value-key": "[SAVG]", "description": "Output stacked avg maps on <qtarget> for all fwhm levels", "type": "String"}, {"name": "stack_rate", "id": "stack_rate", "optional": false, "value-key": "[SRATE]", "description": "Output stacked rate maps on <qtarget> for all fwhm levels", "type": "String"}, {"name": "stack_pc1fit", "id": "stack_pc1fit", "optional": false, "value-key": "[SPC1FIT]", "description": "Output stacked pc1fit maps on <qtarget> for all fwhm levels", "type": "String"}, {"name": "stack_pc1", "id": "stack_pc1", "optional": false, "value-key": "[SPC1]", "description": "Output stacked pc1 maps on <qtarget> for all fwhm levels", "type": "String"}, {"name": "stack_spc", "id": "stack_spc", "optional": false, "value-key": "[SSPC]", "description": "Output stacked spc maps on <qtarget> for all fwhm levels", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p76fq6hqd0mqc4tkfb", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7900731", "title": "FreeSurfer6-mri_glmfit_3con", "description": "Performs general linear model (GLM) analysis in the volume or the surface (https://surfer.nmr.mgh.harvard.edu/fswiki/mri_glmfit).", "publicationdate": "2023-05-05", "deprecated": false, "downloads": 10, "author": "Laboratory for Computational Neuroimaging ", "version": "v6.0.1", "doi": "10.5281/zenodo.7900731", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer6-mri_glmfit_3con", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_6.0.1", "type": "singularity"}, "toolversion": "v6.0.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; mri_glmfit --fsgd [FSGD] --glmdir [DIR] --y [INPUT] --surf fsaverage [HEMI] --C [CON1] --C [CON2] --C [CON3]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "fsgd", "id": "fsgd", "optional": false, "value-key": "[FSGD]", "description": "fsgd file", "type": "String"}, {"name": "output_dir", "id": "outdir", "optional": false, "value-key": "[DIR]", "description": "output directory", "type": "String"}, {"name": "input", "id": "inputdata", "optional": false, "value-key": "[INPUT]", "description": "input file", "type": "String"}, {"name": "contrast 1", "id": "con1", "optional": false, "value-key": "[CON1]", "description": "please specify contrasts 1", "type": "String"}, {"name": "contrast 2", "id": "con2", "optional": false, "value-key": "[CON2]", "description": "please specify contrasts 2", "type": "String"}, {"name": "contrast 3", "id": "con3", "optional": false, "value-key": "[CON3]", "description": "please specify contrasts 3", "type": "String"}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7c8tp85m18tb46vjn", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.15265989", "title": "fsl_anat fuzzy", "description": "General pipeline for processing anatomical images (e.g. T1-weighted scans) via FSL tools. The stages include reorienting the images to the standard (MNI) orientation [fslreorient2std], automatically cropping the image [robustfov], bias-field correction (RF/B1-inhomogeneity-correction) [FAST], registration to standard space (linear and non-linear) [FLIRT and FNIRT], brain-extraction [FNIRT-based or BET], tissue-type segmentation [FAST], and subcortical structure segmentation [FIRST]", "publicationdate": "2025-04-23", "deprecated": false, "downloads": 10, "author": "Oxford Centre for Functional MRI of the Brain (FMRIB)", "version": "6.0.5", "doi": "10.5281/zenodo.15265989", "schemaversion": "0.5", "container": "docker", "tags": {"domain": ["neuroinformatics", "mri"], "toolbox": "fsl"}, "toolversion": "6.0.5", "name": "fsl_anat", "commandline": "fsl_anat [INPUT_FILE] [INPUT_DIR] [OUTPUT_DIR] [CLOBBER_FLAG] [WEAKBIAS_FLAG] [NO_REORIENT_FLAG] [NO_CROP_FLAG] [NO_BIAS_FLAG] [NO_REGISTRATION_FLAG] [NO_NONLINEAR_REG_FLAG] [NO_SEG_FLAG] [NO_SUBCORTSEG_FLAG] [NO_SEARCH_FLAG] [NO_CLEANUP_FLAG] [BIAS_FIELD_SMOOTHING_VAL] [IMAGE_TYPE] [BET_F_PARAM]", "containerimage": {"image": "yohanchatelain/fsl:6.0.5_fuzzy", "index": "index.docker.io", "type": "docker"}, "inputs": [{"command-line-flag": "-i", "description": "Input image file (for single-image use), such as .nii.gz. Either this or an input dir (-d) must be specified, but not both.", "value-key": "[INPUT_FILE]", "type": "File", "list": false, "optional": true, "id": "infile", "name": "Input file"}, {"command-line-flag": "-d", "description": "Existing input directory (.anat extension) where this script will be run in place. Either this or an input file (-i) must be specified, but not both.", "value-key": "[INPUT_DIR]", "type": "File", "list": false, "optional": true, "id": "indir", "name": "Input Dir"}, {"command-line-flag": "-o", "description": "Specifies the output folder name. Note that the .anat extension is automatically appended.", "default-value": "output_results", "value-key": "[OUTPUT_DIR]", "type": "String", "list": false, "optional": false, "id": "outdir", "name": "Output directory"}, {"command-line-flag": "--clobber", "description": "If .anat directory exist (as specified by -o or default from -i) then delete it and make a new one.", "value-key": "[CLOBBER_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "clobber_flag", "name": "Clobber flag"}, {"command-line-flag": "--weakbias", "description": "Used for images with little and/or smooth bias fields. For images acquired using birdcage coils or on 1.5T scanners, the --weakbias option will be faster and may produce equally good results.", "value-key": "[WEAKBIAS_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "weak_bias", "name": "Weak bias flag"}, {"command-line-flag": "--noreorient", "description": "Turn off step that does reorientation 2 standard (fslreorient2std).", "value-key": "[NO_REORIENT_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_reorient_flag", "name": "No reorienation flag"}, {"command-line-flag": "--nocrop", "description": "Turn off step that does automated cropping (robustfov).", "value-key": "[NO_CROP_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_crop_flag", "name": "No automated cropping flag"}, {"command-line-flag": "--nobias", "description": "Turn off steps that do bias field correction (via FAST).", "value-key": "[NO_BIAS_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_bias_flag", "name": "No bias field correction flag"}, {"command-line-flag": "--noreg", "description": "Turn off steps that do registration to standard (FLIRT and FNIRT).", "value-key": "[NO_REGISTRATION_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_reg_flag", "name": "No registration flag"}, {"command-line-flag": "--nononlinreg", "description": "Turn off step that does non-linear registration (FNIRT).", "value-key": "[NO_NONLINEAR_REG_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_nonlin_reg_flag", "name": "No non-linear registration flag"}, {"command-line-flag": "--noseg", "description": "Turn off step that does tissue-type segmentation (FAST).", "value-key": "[NO_SEG_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_seg_flag", "name": "No tissue-type segmentation flag"}, {"command-line-flag": "--nosubcortseg", "description": "Turn off step that does sub-cortical segmentation (FIRST).", "value-key": "[NO_SUBCORTSEG_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_subcort_seg_flag", "name": "No subcortical segmentation flag"}, {"command-line-flag": "--nosearch", "description": "Specify that linear registration uses the -nosearch option (FLIRT).", "value-key": "[NO_SEARCH_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_search_flag", "name": "No search in linear registration flag"}, {"command-line-flag": "--nocleanup", "description": "Do not remove intermediate files.", "value-key": "[NO_CLEANUP_FLAG]", "type": "Flag", "list": false, "optional": true, "id": "no_cleanup_flag", "name": "No cleanup flag"}, {"command-line-flag": "-s", "description": "Specify the value for bias field smoothing (the -l option in FAST).", "value-key": "[BIAS_FIELD_SMOOTHING_VAL]", "type": "Number", "list": false, "optional": true, "id": "bias_field_smoothing_val", "name": "Bias field smoothing value"}, {"command-line-flag": "-t", "description": "Specify the type of image (choose one of T1 T2 PD - default is T1).", "value-key": "[IMAGE_TYPE]", "type": "String", "list": false, "value-choices": ["T1", "T2", "PD"], "optional": true, "id": "image_type", "name": "Image type"}, {"command-line-flag": "--betfparam", "description": "specify the f parameter for BET (only used if not running non-linear reg and also wanting brain extraction done).", "value-key": "[BET_F_PARAM]", "type": "Number", "list": false, "requires-inputs": ["no_nonlin_reg_flag"], "maximum": 1, "minimum": 0, "command-line-flag-separator": "=", "optional": true, "id": "bet_f_param", "name": "F-parameter value for BET"}], "groups": [{"description": "Either a single structural image file (e.g. .nii.gz) or directory (.anat extension) may be given as input", "one-is-required": true, "mutually-exclusive": true, "members": ["infile", "indir"], "id": "group_1", "name": "Input Data"}, {"description": "Parameters for controlling the execution of the fsl_anat task", "id": "group_2", "members": ["clobber_flag", "weak_bias", "no_reorient_flag", "no_crop_flag", "no_bias_flag", "no_reg_flag", "no_nonlin_reg_flag", "no_seg_flag", "no_subcort_seg_flag", "no_search_flag", "no_cleanup_flag", "bias_field_smoothing_val", "image_type", "bet_f_param"], "name": "Optional Parameters"}], "outputfiles": [{"description": "A folder containing the output files for fsl_anat. Includes outputs for the images, reorientation, cropping, bias correction, registration, brain extraction, and segmentation.", "list": false, "id": "folder_out", "optional": false, "path-template": "[OUTPUT_DIR].anat", "name": "Output folder"}], "suggestedresources": {"walltime-estimate": 16000}, "onlineplatformurls": ["https://portal.cbrain.mcgill.ca"], "ark_id": "https://n2t.net/ark:/70798/p7965pd2q9p7z6rsxw", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7893798", "title": "FreeSurfer5-mri_glmfit_3con", "description": "Performs general linear model (GLM) analysis in the volume or the surface (https://surfer.nmr.mgh.harvard.edu/fswiki/mri_glmfit).", "publicationdate": "2023-05-03", "deprecated": false, "downloads": 9, "author": "Laboratory for Computational Neuroimaging ", "version": "v5.3", "doi": "10.5281/zenodo.7893798", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer5-mri_glmfit_3con", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_5.3", "type": "singularity"}, "toolversion": "v5.3", "commandline": "export SUBJECTS_DIR=`pwd`; mri_glmfit --fsgd [FSGD] --glmdir [DIR] --y [INPUT] --surf fsaverage [HEMI] --C [CON1] --C [CON2] --C [CON3]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "fsgd", "id": "fsgd", "optional": false, "value-key": "[FSGD]", "description": "fsgd file", "type": "String"}, {"name": "output_dir", "id": "outdir", "optional": false, "value-key": "[DIR]", "description": "output directory", "type": "String"}, {"name": "input", "id": "inputdata", "optional": false, "value-key": "[INPUT]", "description": "input file", "type": "String"}, {"name": "contrast 1", "id": "con1", "optional": false, "value-key": "[CON1]", "description": "please specify contrasts 1", "type": "String"}, {"name": "contrast 2", "id": "con2", "optional": false, "value-key": "[CON2]", "description": "please specify contrasts 2", "type": "String"}, {"name": "contrast 3", "id": "con3", "optional": false, "value-key": "[CON3]", "description": "please specify contrasts 3", "type": "String"}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7cr1zhs511qf2w6fg", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7458977", "title": "FreeSurfer-freeview", "description": "Save screenshot using freeview to file.", "publicationdate": "2022-12-19", "deprecated": false, "downloads": 9, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.1.1", "doi": "10.5281/zenodo.7458977", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer-freeview", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_7.1.10", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; freeview -f [FILE] -viewport [VIEW] -colorscale -ss [OUTNAME] 1 autotrim", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "image file", "id": "imgfile", "optional": false, "value-key": "[FILE]", "description": "file", "type": "String"}, {"name": "view", "id": "view", "optional": false, "value-key": "[VIEW]", "description": "view", "type": "String", "value-choices": ["3D", "sagittal", "coronal", "axial"]}, {"name": "output file name", "id": "outname", "optional": false, "value-key": "[OUTNAME]", "description": "outname", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p78zknmk013kn89tpg", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7579820", "title": "FreeSurfer-Recon-all_v5", "description": "Performs all, or any part of, the FreeSurfer cortical reconstruction process (https://surfer.nmr.mgh.harvard.edu/fswiki/recon-all).", "publicationdate": "2023-01-28", "deprecated": false, "downloads": 9, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.3.2", "doi": "10.5281/zenodo.7579820", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "suggestedresources": {"ram": 10240, "walltime-estimate": 960, "cpu-cores": 1}, "outputfiles": [{"name": "Output", "optional": false, "description": "The subject data upon which to operate ", "id": "subjid_output", "path-template": "[SUBJID]"}], "name": "FreeSurfer-Recon-all_v5", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_5.3", "type": "singularity"}, "toolversion": "v7.3.2", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; recon-all [SUBJID] [INPUT] [DIRECTIVES] [QCACHE] [MPRAGE] [3T] [CW256] [NOTAL-CHECK] [HYPPOCAMPAL-SUBFIELDS] [BRAINSTEM-STRUCTURES] [NO-WSGCAATLAS] [NO-SKULLSTRIP]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "Output name", "command-line-flag": "-subjid", "optional": false, "value-key": "[SUBJID]", "type": "String", "id": "subjid"}, {"name": "NIFTI file", "id": "input", "optional": false, "value-key": "[INPUT]", "description": "Single NIFTI file from series.", "command-line-flag": "-i", "type": "File"}, {"name": "Directive", "default-value": "-all", "value-key": "[DIRECTIVES]", "optional": false, "type": "String", "id": "directives", "value-choices": ["-all", "-autorecon1", "-autorecon2", "-autorecon2-cp", "-autorecon2-wm", "-autorecon2-inflate1", "-autorecon2-perhemi", "-autorecon3"]}, {"name": "qcache", "id": "qcache_flag", "optional": true, "value-key": "[QCACHE]", "description": "Produce the pre-cached files required by the Qdec utility, allowing rapid analysis of group data.", "command-line-flag": "-qcache", "type": "Flag"}, {"name": "mprage", "id": "mprage_flag", "optional": true, "value-key": "[MPRAGE]", "description": "Assume scan parameters are MGH MP-RAGE protocol.", "command-line-flag": "-mprage", "type": "Flag"}, {"name": "3T", "id": "3T_flag", "optional": true, "value-key": "[3T]", "description": "The -3T flag enables two specific options in recon-all for images acquired with a 3T scanner:  3T-specific NU intensity correction parameters are used in the Non-Uniform normalization stage, and the Schwartz 3T atlas is used for Talairach alignment", "command-line-flag": "-3T", "type": "Flag"}, {"name": "cw256", "id": "cw256_flag", "optional": true, "value-key": "[CW256]", "description": "Include this flag after -autorecon1 if images have a FOV > 256.", "command-line-flag": "-cw256", "type": "Flag"}, {"name": "Notal check", "id": "notal_flag", "optional": true, "value-key": "[NOTAL-CHECK]", "description": "Skip the automatic failure detection of Talairach alignment.", "command-line-flag": "-notal-check", "type": "Flag"}, {"name": "Hippocampal-subfileds-T1", "id": "hippocampal_subfields_T1_flag", "optional": true, "value-key": "[HYPPOCAMPAL-SUBFIELDS]", "description": "Segmentation of hippocampal subfields using input T1 scan.", "command-line-flag": "-hippocampal-subfields-T1", "type": "Flag"}, {"name": "Brainstem Structures", "id": "brainstem_structures_flag", "optional": true, "value-key": "[BRAINSTEM-STRUCTURES]", "description": "Segmentation of brainstem structures.", "command-line-flag": "-brainstem-structures", "type": "Flag"}, {"name": "No wsgcaatlas", "id": "no_wsgcaatlas_flag", "optional": true, "value-key": "[NO-WSGCAATLAS]", "description": "Do not use GCA atlas when skull stripping.", "command-line-flag": "-no-wsgcaatlas", "type": "Flag"}, {"name": "No skull strip", "id": "noskullstrip_flag", "optional": true, "value-key": "[NO-SKULLSTRIP]", "description": "Exclude skull strip step.", "command-line-flag": "-noskullstrip", "type": "Flag"}], "ark_id": "https://n2t.net/ark:/70798/p74djsjmh1g1n1fqvm", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7920888", "title": "FreeSurfer7-mris_preproc", "description": "Concatenate surface-based data with mris_preproc (https://surfer.nmr.mgh.harvard.edu/fswiki/mris_preproc).", "publicationdate": "2023-05-10", "deprecated": false, "downloads": 9, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.3.2", "doi": "10.5281/zenodo.7920888", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer7-mris_preproc", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_7.3.2", "type": "singularity"}, "toolversion": "v7.3.2", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; mris_preproc --fsgd [FSGD] --cache-in [CACHEIN] --target [TARGET] --hemi [HEMI] --out [OUT]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "fsgd", "id": "fsgd", "optional": false, "value-key": "[FSGD]", "description": "fsgd file", "type": "String"}, {"name": "cache-in", "id": "cachein", "optional": false, "value-key": "[CACHEIN]", "description": "cache-in", "type": "String"}, {"name": "target", "id": "target", "optional": false, "value-key": "[TARGET]", "description": "target", "type": "String"}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}, {"name": "out", "id": "out", "optional": false, "value-key": "[OUT]", "description": "output directory", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p74nm84ng1ckr2qpdq", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7900700", "title": "FreeSurfer6-Recon-all-base", "description": "create an unbiased template from all time points for each subject and process it with recon-all -base: (https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalProcessing).", "publicationdate": "2023-05-05", "deprecated": false, "downloads": 9, "author": "Laboratory for Computational Neuroimaging ", "version": "v6.0.1", "doi": "10.5281/zenodo.7900700", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "outputfiles": [{"name": "Output", "optional": false, "description": "output directory", "id": "output", "path-template": "[OUTPUTDIR]"}], "name": "FreeSurfer6-Recon-all-base", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_6.0.1", "type": "singularity"}, "toolversion": "v6.0.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; recon-all -base [OUTPUTDIR] -tp [TP1] -tp [TP2] -all", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "Output name", "optional": false, "value-key": "[OUTPUTDIR]", "type": "String", "id": "outputdir"}, {"name": "timepoint_1", "optional": false, "value-key": "[TP1]", "description": "Input directory timepoint 1", "type": "String", "id": "tp1"}, {"name": "timepoint_2", "optional": false, "value-key": "[TP2]", "description": "Input directory timepoint 2", "type": "String", "id": "tp2"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p78zhjcgw60rc8mswq", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7900745", "title": "FreeSurfer6-mris_preproc", "description": "Concatenate surface-based data with mris_preproc (https://surfer.nmr.mgh.harvard.edu/fswiki/mris_preproc).", "publicationdate": "2023-05-05", "deprecated": false, "downloads": 9, "author": "Laboratory for Computational Neuroimaging ", "version": "v6.0.1", "doi": "10.5281/zenodo.7900745", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer6-mris_preproc", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_6.0.1", "type": "singularity"}, "toolversion": "v6.0.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; mris_preproc --fsgd [FSGD] --cache-in [CACHEIN] --target [TARGET] --hemi [HEMI] --out [OUT]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "fsgd", "id": "fsgd", "optional": false, "value-key": "[FSGD]", "description": "fsgd file", "type": "String"}, {"name": "cache-in", "id": "cachein", "optional": false, "value-key": "[CACHEIN]", "description": "cache-in", "type": "String"}, {"name": "target", "id": "target", "optional": false, "value-key": "[TARGET]", "description": "target", "type": "String"}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}, {"name": "out", "id": "out", "optional": false, "value-key": "[OUT]", "description": "output directory", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p72v81xg44xw046xx4", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.8365022", "title": "Freesurfer mris_compute_lgi", "description": "Performs mris_compute_lgi.", "publicationdate": "2023-09-20", "deprecated": false, "downloads": 9, "author": "Laboratory for Computational Neuroimaging ", "version": "unknown", "doi": "10.5281/zenodo.8365022", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer-mri_glmfit-sim", "containerimage": {"index": "docker://", "image": "freesurfer/freesurfer:7.1.1", "type": "singularity"}, "toolversion": "v7.1.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; mris_compute_lgi --i [INPUT]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "input", "id": "input", "optional": true, "value-key": "[INPUT]", "description": "Input surface file, typically lh.pial or rh.pial", "type": "String"}], "custom": {"cbrain:author": "Nigel Yong <hey@nigelyong.com>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7h70gvfq5mcv6brvz", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7920896", "title": "FreeSurfer7-mri_glmfit-sim", "description": "Performs general linear model (GLM) analysis in the volume or the surface with correction for multiple comparisons (https://surfer.nmr.mgh.harvard.edu/fswiki/mri_glmfit).", "publicationdate": "2023-05-10", "deprecated": false, "downloads": 9, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.3.2", "doi": "10.5281/zenodo.7920896", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer7-mri_glmfit-sim", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_7.3.2", "type": "singularity"}, "toolversion": "v7.3.2", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; mri_glmfit-sim --glmdir [DIR] --cache [CACHE_abs] abs --cwp [CWP] --2spaces", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "glm_dir", "id": "dir", "optional": false, "value-key": "[DIR]", "description": "glm directory", "type": "String"}, {"name": "CACHE_abs", "id": "CACHE_abs", "optional": false, "value-key": "[CACHE_abs]", "description": "vertex-wise cluster threshold for both contrasts", "type": "String"}, {"name": "cwp", "id": "cwp", "optional": false, "value-key": "[CWP]", "description": "cluster-wise p-threshold", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7ktw0rgc9frm0ph1r", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7900735", "title": "FreeSurfer6-mri_glmfit-sim", "description": "Performs general linear model (GLM) analysis in the volume or the surface with correction for multiple comparisons (https://surfer.nmr.mgh.harvard.edu/fswiki/mri_glmfit).", "publicationdate": "2023-05-05", "deprecated": false, "downloads": 8, "author": "Laboratory for Computational Neuroimaging ", "version": "v6.0.1", "doi": "10.5281/zenodo.7900735", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer6-mri_glmfit-sim", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_6.0.1", "type": "singularity"}, "toolversion": "v6.0.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; mri_glmfit-sim --glmdir [DIR] --cache [CACHE_abs] abs --cwp [CWP] --2spaces", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "glm_dir", "id": "dir", "optional": false, "value-key": "[DIR]", "description": "glm directory", "type": "String"}, {"name": "CACHE_abs", "id": "CACHE_abs", "optional": false, "value-key": "[CACHE_abs]", "description": "vertex-wise cluster threshold for both contrasts", "type": "String"}, {"name": "cwp", "id": "cwp", "optional": false, "value-key": "[CWP]", "description": "cluster-wise p-threshold", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7xgt4nrf9wv120fqf", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.14766184", "title": "CQUEST", "description": "MR spectrosocpy signal quantification software", "publicationdate": "2025-01-29", "deprecated": false, "downloads": 8, "author": "H\u00e9l\u00e8ne RATINEY", "version": "0.6", "doi": "10.5281/zenodo.14766184", "schemaversion": "0.5", "container": "docker", "tags": "Boutiques", "name": "CQUEST", "toolversion": "0.6", "commandline": "unzip [MYZIP] ; /cquest_exec/cquestCml [PARAM_FILE] [DATA_FILE] > stdout_cquest.txt ; cat stdout_cquest.txt; tar -czvf [OUT_FILE] [DATA_FILE] *quest_estim.mrui *quest_back.mrui *.txt", "containerimage": {"image": "preproc_cquest:0.6", "index": "hub.docker.com", "type": "docker"}, "inputs": [{"id": "parameter_file", "name": "Parameter text file", "type": "File", "description": "File setting up constraints, options and prior knowledge used in cQuest algorithm", "value-key": "[PARAM_FILE]", "list": false, "optional": false, "command-line-flag": "-f"}, {"id": "data_file", "name": "DATA file", "type": "File", "description": "File with extension and format of jMRUI containing the signal to quantify", "value-key": "[DATA_FILE]", "list": false, "optional": false, "command-line-flag": ""}, {"id": "zipped_folder", "name": "Zipped data base folder", "type": "File", "description": "Archive containing the files listed in the parameter file", "value-key": "[MYZIP]", "list": false, "optional": false, "command-line-flag": ""}], "outputfiles": [{"description": "A tarball containing all result files", "id": "output_file", "list": false, "name": "Output file", "value-key": "[OUT_FILE]", "path-template": "[DATA_FILE]--[PARAM_FILE].tgz"}], "ark_id": "https://n2t.net/ark:/70798/p70h16fxk8g6199vjd", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7920892", "title": "FreeSurfer7-mri_glmfit_1con", "description": "Performs general linear model (GLM) analysis in the volume or the surface (https://surfer.nmr.mgh.harvard.edu/fswiki/mri_glmfit).", "publicationdate": "2023-05-10", "deprecated": false, "downloads": 8, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.3.2", "doi": "10.5281/zenodo.7920892", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer7-mri_glmfit_1con", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_7.3.2", "type": "singularity"}, "toolversion": "v7.3.2", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; mri_glmfit --fsgd [FSGD] --glmdir [DIR] --y [INPUT] --surf fsaverage [HEMI] --C [CON]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "fsgd", "id": "fsgd", "optional": false, "value-key": "[FSGD]", "description": "fsgd file", "type": "String"}, {"name": "output_dir", "id": "outdir", "optional": false, "value-key": "[DIR]", "description": "output directory", "type": "String"}, {"name": "input", "id": "inputdata", "optional": false, "value-key": "[INPUT]", "description": "input file", "type": "String"}, {"name": "contrast", "id": "con", "optional": false, "value-key": "[CON]", "description": "please specify contrast", "type": "String"}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7pn934ds149v81v13", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.12773399", "title": "CQUESTwithBruker-preproc", "description": "Proprocessing pipeline for spectroscopy signals acquired on a Brucker MRI followed by cQuest MR spectrosocpy signal quantification software.<br />", "publicationdate": "2024-07-18", "deprecated": false, "downloads": 8, "author": "H\u00e9l\u00e8ne RATINEY / Denis Grenier / Th\u00e9otime Ferh--Delude", "version": "0.6", "doi": "10.5281/zenodo.12773399", "schemaversion": "0.5", "container": "docker", "tags": "Boutiques", "name": "CQUESTwithBruker-preproc", "toolversion": "0.6", "containerimage": {"index": "docker://", "image": "preproc_cquest:0.6", "type": "docker"}, "commandline": "mkdir out; unzip [MYZIP]; metaboliteFile=$(grep -m 1 '^met=' [PARAM_FILE] | cut -d ' ' -f1 | cut -d '=' -f2); python3 /bruker-spectro-processing-pipeline/vip_prepro.py [FIDFILE] [ACQPFILE] [METHODFILE] [REFSCANFILE] [RAWJOB0FILE] [PPM_R] [PPM_A] [NOISE_R] [DISPLAY_R] [MEAN_LW] [STDEV_LW] [STDEV_FR] [MV_AV] --metabolite $metaboliteFile --outname [OUTNAME] --outpath ./; echo \"Preprocessing finished, listing files and launching cQuest\"; ls ; /cquest_exec/cquestCml -f [PARAM_FILE] [BRUKER_MRUI]; /cquest_exec/cquestCml -f [PARAM_FILE] [PASTIS_MRUI]", "inputs": [{"id": "fid", "name": "fid", "type": "File", "description": "Path to the fid file", "command-line-flag": "--fid", "value-key": "[FIDFILE]", "optional": false}, {"id": "acqp", "name": "acqp", "type": "File", "command-line-flag": "--acqp", "description": "Acqp file", "value-key": "[ACQPFILE]", "optional": false}, {"id": "method", "name": "method", "type": "File", "command-line-flag": "--method", "description": "method file", "value-key": "[METHODFILE]", "optional": false}, {"id": "refscan", "name": "refscan", "type": "File", "description": "Path to the fid.refscan file", "command-line-flag": "--refscan", "value-key": "[REFSCANFILE]", "optional": false}, {"id": "rawjob0", "name": "rawjob0", "type": "File", "description": "Path to the rawdata.job0 file", "command-line-flag": "--rawjob0", "value-key": "[RAWJOB0FILE]", "optional": false}, {"id": "outname", "name": "outname", "type": "String", "description": "Name of the output file", "value-key": "[OUTNAME]", "optional": false}, {"id": "parameter_file", "name": "Parameter text file for cQuest", "type": "File", "description": "File setting up constraints, options and prior knowledge used in cQuest algorithm", "value-key": "[PARAM_FILE]", "list": false, "optional": false}, {"id": "zipped_folder", "name": "Zipped data base folder for cQuest", "type": "File", "description": "Archive containing the files listed in the parameter file", "value-key": "[MYZIP]", "list": false, "optional": false, "command-line-flag": ""}, {"id": "ppm_r", "name": "ppm_r", "type": "String", "optional": true, "default-value": "1.9_2.1", "description": "MUST be an interval in the format start_end   . frequency region in ppm on which phasing operations are focused.", "command-line-flag": "--ppm_r", "value-key": "[PPM_R]"}, {"id": "ppm_a", "name": "ppm_a", "type": "String", "optional": true, "default-value": "1.9_2.1", "description": "MUST be an interval in the format start_end   . frequency region in ppm on which SNR and LW analysis are performed (NAA peak).", "command-line-flag": "--ppm_a", "value-key": "[PPM_A]"}, {"id": "noise_r", "name": "noise_r", "type": "String", "optional": true, "default-value": "5.5_6", "description": "MUST be an interval in the format start_end   . frequency region in ppm on which noise level is estimated", "command-line-flag": "--noise_r", "value-key": "[NOISE_R]"}, {"id": "display_r", "name": "display_r", "type": "String", "optional": true, "default-value": "0.5_5", "description": "MUST be an interval in the format start_end   . frequency region in ppm used to display the spectra", "command-line-flag": "--display_r", "value-key": "[DISPLAY_R]"}, {"id": "mean_lw_Hz", "name": "mean_lw_Hz", "type": "Number", "optional": true, "default-value": 20, "description": "Mean linewidth considered as good linewidth for further analysis (Hz)", "command-line-flag": "--mean_lw_Hz", "value-key": "[MEAN_LW]"}, {"id": "stdev_lw_Hz", "name": "stdev_lw_Hz", "type": "Number", "optional": true, "default-value": 2, "description": "acceptable standard deviation around the mean linewidth (Hz)", "command-line-flag": "--stdev_lw_Hz", "value-key": "[STDEV_LW]"}, {"id": "stdev_fr_ppm", "name": "stdev_fr_ppm", "type": "Number", "optional": true, "default-value": 0.03, "description": "acceptable standard deviation/amplitude of the frequency fluctuation/drift in ppm", "command-line-flag": "--stdev_fr_ppm", "value-key": "[STDEV_FR]"}, {"id": "mv_av", "name": "mv_av", "type": "Number", "integer": true, "optional": true, "default-value": 11, "description": "number of spectra in a moving average used in the analyze and reject procedure", "command-line-flag": "--mv_av", "value-key": "[MV_AV]"}], "outputfiles": [{"description": "Pastis MRUI reconstructed data", "id": "mrui_pastis", "list": false, "name": "Pastis MRUI Reconstructed", "value-key": "[PASTIS_MRUI]", "path-template": "[OUTNAME]RecPastis.mrui"}, {"description": "Bruker MRUI reconstructed data", "id": "mrui_bruker", "list": false, "name": "Pastis MRUI Reconstructed", "value-key": "[BRUKER_MRUI]", "path-template": "[OUTNAME]RecBruker.mrui"}, {"description": "Pastis RAW reconstructed data", "id": "raw_pastis", "list": false, "name": "Pastis MRUI Reconstructed", "path-template": "[OUTNAME]RecPastis.RAW"}, {"description": "Bruker RAW reconstructed data", "id": "raw_bruker", "list": false, "name": "Pastis MRUI Reconstructed", "path-template": "[OUTNAME]RecBruker.RAW"}, {"description": "PDF reconstruction summary", "id": "pdf", "list": false, "name": "PDF", "path-template": "[OUTNAME]-summary.pdf"}, {"description": "CQUEST output for Pastis MRUI", "id": "cquest_pastis", "list": false, "name": "CQUEST pastis", "path-template": "[OUTNAME]RecPastis_quest2.txt"}, {"description": "CQUEST output for Bruker MRUI", "id": "cquest_bruker", "list": false, "name": "CQUEST bruker", "path-template": "[OUTNAME]RecBruker_quest2.txt"}], "custom": {"vip:dotInputs": ["results-directory", "fid", "acqp", "method", "refscan", "rawjob0", "outname"]}, "ark_id": "https://n2t.net/ark:/70798/p7c6f6sr97ngh0h92m", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7893796", "title": "FreeSurfer5-mri_glmfit_1con", "description": "Performs general linear model (GLM) analysis in the volume or the surface (https://surfer.nmr.mgh.harvard.edu/fswiki/mri_glmfit).", "publicationdate": "2023-05-03", "deprecated": false, "downloads": 8, "author": "Laboratory for Computational Neuroimaging ", "version": "v5.3", "doi": "10.5281/zenodo.7893796", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer5-mri_glmfit_1con", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_5.3", "type": "singularity"}, "toolversion": "v5.3", "commandline": "export SUBJECTS_DIR=`pwd`; mri_glmfit --fsgd [FSGD] --glmdir [DIR] --y [INPUT] --surf fsaverage [HEMI] --C [CON]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "fsgd", "id": "fsgd", "optional": false, "value-key": "[FSGD]", "description": "fsgd file", "type": "String"}, {"name": "output_dir", "id": "outdir", "optional": false, "value-key": "[DIR]", "description": "output directory", "type": "String"}, {"name": "input", "id": "inputdata", "optional": false, "value-key": "[INPUT]", "description": "input file", "type": "String"}, {"name": "contrast", "id": "con", "optional": false, "value-key": "[CON]", "description": "please specify contrast", "type": "String"}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7zv3z4s60s6n4xvqz", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7884225", "title": "FreeSurfer5-Recon-all-long", "description": "-long longitudinally process all timepoints with recon-all -long: (https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalProcessing).", "publicationdate": "2023-05-01", "deprecated": false, "downloads": 8, "author": "Laboratory for Computational Neuroimaging ", "version": "v5.3", "doi": "10.5281/zenodo.7884225", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer5-Recon-all-long", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_5.3", "type": "singularity"}, "toolversion": "v5.3", "commandline": "export SUBJECTS_DIR=`pwd`; recon-all -long [TP] [BASE] -all", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "timepoint", "id": "tp", "optional": false, "value-key": "[TP]", "description": "input timepoint", "type": "String"}, {"name": "base template", "id": "base", "optional": false, "value-key": "[BASE]", "description": "subject template", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p797x6j9511bf6zvnp", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7920788", "title": "FreeSurfer7-Recon-all-long", "description": "-long longitudinally process all timepoints with recon-all -long: (https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalProcessing).", "publicationdate": "2023-05-10", "deprecated": false, "downloads": 8, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.3.2", "doi": "10.5281/zenodo.7920788", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer7-Recon-all-long", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_7.3.2", "type": "singularity"}, "toolversion": "v7.3.2", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; recon-all -long [TP] [BASE] -all", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "timepoint", "id": "tp", "optional": false, "value-key": "[TP]", "description": "input timepoint", "type": "String"}, {"name": "base template", "id": "base", "optional": false, "value-key": "[BASE]", "description": "subject template", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p76t7wp6r8qr12283f", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7920894", "title": "FreeSurfer7-mri_glmfit_3con", "description": "Performs general linear model (GLM) analysis in the volume or the surface (https://surfer.nmr.mgh.harvard.edu/fswiki/mri_glmfit).", "publicationdate": "2023-05-10", "deprecated": false, "downloads": 7, "author": "Laboratory for Computational Neuroimaging ", "version": "v7.3.2", "doi": "10.5281/zenodo.7920894", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer7-mri_glmfit_3con", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_7.3.2", "type": "singularity"}, "toolversion": "v7.3.2", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; mri_glmfit --fsgd [FSGD] --glmdir [DIR] --y [INPUT] --surf fsaverage [HEMI] --C [CON1] --C [CON2] --C [CON3]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "fsgd", "id": "fsgd", "optional": false, "value-key": "[FSGD]", "description": "fsgd file", "type": "String"}, {"name": "output_dir", "id": "outdir", "optional": false, "value-key": "[DIR]", "description": "output directory", "type": "String"}, {"name": "input", "id": "inputdata", "optional": false, "value-key": "[INPUT]", "description": "input file", "type": "String"}, {"name": "contrast 1", "id": "con1", "optional": false, "value-key": "[CON1]", "description": "please specify contrasts 1", "type": "String"}, {"name": "contrast 2", "id": "con2", "optional": false, "value-key": "[CON2]", "description": "please specify contrasts 2", "type": "String"}, {"name": "contrast 3", "id": "con3", "optional": false, "value-key": "[CON3]", "description": "please specify contrasts 3", "type": "String"}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7p76bgjf6gq909kkf", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7893807", "title": "FreeSurfer5-mri_glmfit-sim", "description": "Performs general linear model (GLM) analysis in the volume or the surface with correction for multiple comparisons (https://surfer.nmr.mgh.harvard.edu/fswiki/mri_glmfit).", "publicationdate": "2023-05-03", "deprecated": false, "downloads": 7, "author": "Laboratory for Computational Neuroimaging ", "version": "v5.3", "doi": "10.5281/zenodo.7893807", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer5-mri_glmfit-sim", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_5.3", "type": "singularity"}, "toolversion": "v5.3", "commandline": "export SUBJECTS_DIR=`pwd`; mri_glmfit-sim --glmdir [DIR] --cache [CACHE_abs] abs --cwp [CWP] --2spaces", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "glm_dir", "id": "dir", "optional": false, "value-key": "[DIR]", "description": "glm directory", "type": "String"}, {"name": "CACHE_abs", "id": "CACHE_abs", "optional": false, "value-key": "[CACHE_abs]", "description": "vertex-wise cluster threshold for both contrasts", "type": "String"}, {"name": "cwp", "id": "cwp", "optional": false, "value-key": "[CWP]", "description": "cluster-wise p-threshold", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7w7tbz881shw2t747", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7893178", "title": "FreeSurfer-long_mris_slopes", "description": "Prepare the data with long_mris_slopes for longitudinal two stage model (https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalTwoStageModel).", "publicationdate": "2023-05-03", "deprecated": false, "downloads": 7, "author": "Laboratory for Computational Neuroimaging ", "version": "v5.3", "doi": "10.5281/zenodo.7893178", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer-long_mris_slopes", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_5.3", "type": "singularity"}, "toolversion": "v5.3", "commandline": "export SUBJECTS_DIR=`pwd`; long_mris_slopes --qdec [QDEC] --meas [MEASURE] --hemi [HEMI] --do-avg --do-rate --do-pc1 --do-pc1fit --do-spc --do-stack --do-label --time [TIME] --qcache fsaverage --sd $SUBJECTS_DIR --stack-avg [SAVG] --stack-rate [SRATE] --stack-pc1fit [SPC1FIT] --stack-pc1 [SPC1] --stack-spc [SSPC]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "qdec table", "id": "qdec", "optional": false, "value-key": "[QDEC]", "description": "qdec table", "type": "String"}, {"name": "measure", "id": "meas", "optional": false, "value-key": "[MEASURE]", "description": "measure", "type": "String", "value-choices": ["thickness", "volume"]}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}, {"name": "time", "id": "time", "optional": false, "value-key": "[TIME]", "description": "time variable in qdec table", "type": "String"}, {"name": "stack_avg", "id": "stack_avg", "optional": false, "value-key": "[SAVG]", "description": "Output stacked avg maps on <qtarget> for all fwhm levels", "type": "String"}, {"name": "stack_rate", "id": "stack_rate", "optional": false, "value-key": "[SRATE]", "description": "Output stacked rate maps on <qtarget> for all fwhm levels", "type": "String"}, {"name": "stack_pc1fit", "id": "stack_pc1fit", "optional": false, "value-key": "[SPC1FIT]", "description": "Output stacked pc1fit maps on <qtarget> for all fwhm levels", "type": "String"}, {"name": "stack_pc1", "id": "stack_pc1", "optional": false, "value-key": "[SPC1]", "description": "Output stacked pc1 maps on <qtarget> for all fwhm levels", "type": "String"}, {"name": "stack_spc", "id": "stack_spc", "optional": false, "value-key": "[SSPC]", "description": "Output stacked spc maps on <qtarget> for all fwhm levels", "type": "String"}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p7s9q57rm6qcx8dxtj", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.7900725", "title": "FreeSurfer6-mri_glmfit_1con", "description": "Performs general linear model (GLM) analysis in the volume or the surface (https://surfer.nmr.mgh.harvard.edu/fswiki/mri_glmfit).", "publicationdate": "2023-05-05", "deprecated": false, "downloads": 7, "author": "Laboratory for Computational Neuroimaging ", "version": "v6.0.1", "doi": "10.5281/zenodo.7900725", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "FreeSurfer6-mri_glmfit_1con", "containerimage": {"index": "docker://", "image": "ansokol/freesurfer_6.0.1", "type": "singularity"}, "toolversion": "v6.0.1", "commandline": "export SUBJECTS_DIR=`pwd`; export FS_LICENSE=`pwd`/[LICENSE_FILE]; mri_glmfit --fsgd [FSGD] --glmdir [DIR] --y [INPUT] --surf fsaverage [HEMI] --C [CON]", "errorcodes": [{"description": "Crashed", "code": 1}], "inputs": [{"name": "License file", "value-key": "[LICENSE_FILE]", "optional": false, "description": "Valid license file needed to run FreeSurfer.", "id": "license", "type": "File"}, {"name": "fsgd", "id": "fsgd", "optional": false, "value-key": "[FSGD]", "description": "fsgd file", "type": "String"}, {"name": "output_dir", "id": "outdir", "optional": false, "value-key": "[DIR]", "description": "output directory", "type": "String"}, {"name": "input", "id": "inputdata", "optional": false, "value-key": "[INPUT]", "description": "input file", "type": "String"}, {"name": "contrast", "id": "con", "optional": false, "value-key": "[CON]", "description": "please specify contrast", "type": "String"}, {"name": "hemisphere", "id": "hemi", "optional": false, "value-key": "[HEMI]", "description": "hemisphere", "type": "String", "value-choices": ["lh", "rh"]}], "custom": {"cbrain:author": "Andrzej Sokolowski <andrzej.sokolowski@concordia.ca>", "cbrain:readonly-input-files": true}, "ark_id": "https://n2t.net/ark:/70798/p71cc86bw9xx997nbz", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.14008350", "title": "pyLossless", "description": "Run the pyLossless pipeline on a BIDS subject file.", "publicationdate": "2024-10-29", "deprecated": false, "downloads": 7, "author": "Scott Huberty and Tyler Collins <https://github.com/lina-usc/pylossless>", "version": "0.2", "doi": "10.5281/zenodo.14008350", "schemaversion": "0.5", "container": "singularity", "tags": {"domain": ["neuroinformatics", "eeg", "eegnet"]}, "name": "pyLossless", "toolversion": "0.2", "commandline": "pylossless [BDF_INPUT] [SUBJECT_ID] [OUTPUT_PATH]", "containerimage": {"image": "tk11br/pylossless-cbrain:0.2", "index": "docker://", "type": "singularity"}, "inputs": [{"id": "bdf_input", "name": "Single BDF file", "optional": false, "type": "File", "description": "Input BDF file to the pylossless pipeline.", "value-key": "[BDF_INPUT]"}, {"id": "subject_id", "name": "Subject ID", "optional": false, "type": "String", "description": "Subject ID to assign to source file.", "value-key": "[SUBJECT_ID]"}, {"id": "output_path", "name": "Output Path", "optional": false, "type": "String", "description": "Output path to begin writing tool results.", "value-key": "[OUTPUT_PATH]"}], "outputfiles": [{"id": "output_directory", "name": "Output Directory", "optional": true, "description": "Output directory", "path-template": "[OUTPUT_PATH]/derivatives/pylossless"}], "suggestedresources": {"walltime-estimate": 7200, "ram": 16}, "custom": {"cbrain:author": "Tyler Collins <collins.tyler.k@gmail.com>", "cbrain:readonly-input-files": true, "cbrain:integrator_modules": {"BoutiquesInputValueFixer": {"output_path": "cbrain_py_out"}}}, "ark_id": "https://n2t.net/ark:/70798/p7x4gsn08349n8h38m", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.14766170", "title": "LCModel", "description": "MR spectrosocpy signal quantification software", "publicationdate": "2025-01-29", "deprecated": false, "downloads": 6, "author": "H\u00e9l\u00e8ne RATINEY", "version": "0.2", "doi": "10.5281/zenodo.14766170", "schemaversion": "0.5", "container": "docker", "tags": "Boutiques", "name": "LCModel", "toolversion": "0.2", "commandline": "bash /.lcmodel/bin/run-lcmodel.sh [CTRL_FILE] [SIGNAL_FILE] [MAKEBASIS_FILE] [ZIP_DATA] [OUT_FILE]; ps2pdf output/*.ps [PDF_FILE]", "containerimage": {"image": "hratiney/lcmodel:0.2", "index": "hub.docker.com", "type": "docker"}, "inputs": [{"id": "signal_file", "name": "Signal file", "type": "File", "description": "Text file with extension '.RAW' containing the signal to quantify", "value-key": "[SIGNAL_FILE]", "list": false, "optional": false, "command-line-flag": ""}, {"id": "control_file", "name": "Control file", "type": "File", "description": "Text file with extension '.control' setting up constraints, options and prior knowledge used in LCModel algorithm", "value-key": "[CTRL_FILE]", "list": false, "optional": false, "command-line-flag": ""}, {"id": "makebasis_file", "name": "MakeBasis file", "type": "File", "description": "Text file with extension '.in' containing the list of metabolite files given in the zipped data base folder. It is used as input for makebasis, which will generate a .basis file for LCModel", "value-key": "[MAKEBASIS_FILE]", "list": false, "optional": false, "command-line-flag": ""}, {"id": "zipped_folder", "name": "Zipped data base folder", "type": "File", "description": "Archive containing all metabolite & macromolecules in .RAW format", "value-key": "[ZIP_DATA]", "list": false, "optional": false, "command-line-flag": ""}], "outputfiles": [{"description": "A tarball containing all result files", "id": "output_file", "list": false, "name": "Output file", "value-key": "[OUT_FILE]", "path-template": "[SIGNAL_FILE]--[CTRL_FILE].tgz"}, {"description": "PDF result file", "id": "pdf_file", "list": false, "name": "PDF output file", "value-key": "[PDF_FILE]", "path-template": "[SIGNAL_FILE]--[CTRL_FILE].pdf"}], "ark_id": "https://n2t.net/ark:/70798/p7vvw0b3c722t2cjtq", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.14766127", "title": "PWML_Detection_and_Segmentation", "description": "Punctate white matter lesions (PWML) are the most common white matter injuries observed in preterm neonates, with several studies reporting a link between these lesions and adverse long-term outcomes. Automated PWML detection through cranial ultrasound (cUS) imaging could better assist doctors in diagnosis, at a lower cost than MRI. However it is very challenging due to the small size and low contrast of lesions, and the number of lesions can also vary considerably across subjects. With this tool, we propose a two-phase strategy: 1) Segmentation with a vision transformer to increase the numberof detected lesions. 2) Multi-view classification based on cross-attention to reduce the number of false alarms and improve precision. Finally, we also apply multiple postprocessing approaches to ensure the quality of predictions and compare our results with what is known in MRI.", "publicationdate": "2025-01-29", "deprecated": false, "downloads": 6, "author": "Flora Estermann", "version": "v0.3", "doi": "10.5281/zenodo.14766127", "schemaversion": "0.5", "container": "docker", "tags": "Boutiques", "name": "PWML_Detection_and_Segmentation", "toolversion": "v0.3", "commandline": "python3 /app/PWML_Detection_and_Segmentation/main.py -in=[INPUT1] -out=output && mv output/full_brain_image.nrrd [OUTPUT1] && mv output/full_brain_prediction.nrrd [OUTPUT2]", "containerimage": {"image": "pwml_segmentation:v0.3", "index": "docker://", "type": "docker"}, "inputs": [{"id": "input1", "name": "Volume cUS (format .mat)", "description": "Cranial ultrasound (cUS) volume used for PWML prediction (format .mat).", "type": "File", "value-key": "[INPUT1]", "optional": false}], "outputfiles": [{"id": "outfile1", "name": "Volume cUS (format .nrrd)", "description": "Cranial ultrasound (cUS) volume used for prediction and vizualization (format .nrrd).", "optional": false, "path-template": "[INPUT1]-full_brain_image.nrrd", "path-template-stripped-extensions": [".mat"], "value-key": "[OUTPUT1]"}, {"id": "outfile2", "name": "PWML prediction", "description": "Binary volume indicating the location and volume of any PWML predicted by the pipeline (format .nrrd).", "optional": false, "path-template": "[INPUT1]-full_brain_prediction.nrrd", "path-template-stripped-extensions": [".mat"], "value-key": "[OUTPUT2]"}], "ark_id": "https://n2t.net/ark:/70798/p7pfpcz066rcp6zq8n", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}, {"id": "zenodo.15346974", "title": "Agitation", "description": "Deep Learning based tool to quantify subject motion in T1w brain MRI ", "publicationdate": "2025-05-06", "deprecated": false, "downloads": 6, "author": "Neuro-iX, Charles Bricout", "version": "v0.0.2", "doi": "10.5281/zenodo.15346974", "schemaversion": "0.5", "container": "singularity", "tags": "Boutiques", "name": "Agitation", "toolversion": "v0.0.2", "commandline": "agitation inference [BIDS_DIRECTORY] [SUBJECT_ID] [SESSION_ID] [GPU_FLAG] [CUDA_ID] [OUTPUT_DIR]", "containerimage": {"image": "chbricout/agitation:0.0.2", "index": "docker://", "type": "singularity", "container-opts": ["--nv"]}, "inputs": [{"name": "The root BIDS directory", "id": "bids_dir", "type": "File", "optional": false, "value-key": "[BIDS_DIRECTORY]", "command-line-flag": "--bids_dir"}, {"name": "The BIDS subject id (sub-<label>)", "id": "subject_id", "type": "String", "optional": false, "value-key": "[SUBJECT_ID]", "command-line-flag": "--subject_id"}, {"name": "The BIDS session id (ses-<label>)", "id": "session_id", "type": "String", "optional": false, "value-key": "[SESSION_ID]", "command-line-flag": "--session_id"}, {"name": "Flag to use GPU during inference", "id": "gpu", "type": "Flag", "optional": true, "command-line-flag": "-g", "value-key": "[GPU_FLAG]"}, {"name": "The CUDA identifier of the GPU to use (Defaults to 0)", "id": "cuda", "type": "Number", "optional": true, "value-key": "[CUDA_ID]", "command-line-flag": "--cuda"}, {"name": "The output directory for the motion csv", "id": "output_dir", "type": "File", "optional": false, "value-key": "[OUTPUT_DIR]", "command-line-flag": "--output_dir"}], "suggestedresources": {"cpu-cores": 6, "ram": 4, "walltime-estimate": 5}, "errorcodes": [{"code": 1, "description": "Crashed"}], "ark_id": "https://n2t.net/ark:/70798/p75z25qw87s253t9bj", "platforms": [{"img": "/static/img/run_on_cbrain_gray.png", "uri": ""}]}]}