CONP Portal | PREVENT-AD open data in BIDS format


Version: 2.0

Source: https://openpreventad.loris.ca

Authors: StoP-AD Center - Douglas Mental Health University Institute

Contact: Jennifer Tremblay-Mercier, Research Coordinator, jennifer.tremblay-mercier@douglas.mcgill.ca, 514-761-6131 #3329

Description: Longitudinal study of pre-symptomatic Alzheimer's Disease

Licenses: https://openpreventad.loris.ca/images/Open_PREVENT-AD_Terms_of_Use.png

Input Datasets: preventad-open

Primary Publication: Rationale and Structure for a new Centre for Studies on Prevention of Alzheimer's Disease (StoP-AD). John C.S. Breitner et al. The Journal of Prevention of Alzheimer's Disease - JPAD Volume 3, Number 4, 2016. http://dx.doi.org/10.14283/jpad.2016.121

Dataset Download Instructions

CircleCI status

The following instructions require a basic understanding of UNIX/LINUX command lines. Future portal functionality may include downloads directly from the web browser. Dataset download is currently enabled through DataLad.

Note: The conp-dataset requires version >=0.12.5 of DataLad and version >=8.20200309 of git-annex.

To install DataLad on your system, please refer to the install section of the DataLad Handbook (installation via miniconda is recommended in order to obtain the latest version of DataLad).

1) Initiate the CONP dataset

To initiate the CONP dataset (conp-dataset), run the following command in the directory where you want CONP datasets to be installed:

datalad install https://github.com/CONP-PCNO/conp-dataset.git

2) Install the preventad-open-bids dataset

To install the dataset, go into the created conp-dataset directory and run datalad install on the dataset preventad-open-bids:

cd conp-dataset
datalad install projects/preventad-open-bids

3) Download the preventad-open-bids dataset

Now that the DataLad dataset has been installed, go into the dataset directory under projects/preventad-open-bids.

cd projects/preventad-open-bids

Note that files visible in the dataset are symlinks and will need to be downloaded manually using the datalad get command in the dataset directory:

datalad get <filepath>

Note, if you run datalad get * command, all the files present in the dataset directory will be downloaded.

For more information on how DataLad works, please visit the DataLad Handbook documentation .

Dataset README information

README.md

PREVENT-AD open Dataset organized according to the BIDS standard

Overview

This is a derived dataset of preventad-open where all the images are organized according to the BIDS standard. Conversion to NIfTI was performed from the original MINC files available in the preventad-open dataset.

The PREVENT-AD (Pre-symptomatic Evaluation of Experimental or Novel Treatments for Alzheimer Disease) cohort is composed of cognitively healthy participants over 55 years old, at risk of developing Alzheimer Disease (AD) as their parents and/or siblings were/are affected by the disease. These ‘at-risk’ participants have been followed for a naturalistic study of the presymptomatic phase of AD since 2011 using multimodal measurements of various disease indicators. Two clinical trials intended to test pharmaco-preventive agents have also been conducted.

The PREVENT-AD research group is now releasing data openly with the intention to contribute to the community’s growing understanding of AD pathogenesis.

More detailed information about the study design can be found in the LORIS instance of Open PREVENT-AD (https://openpreventad.loris.ca).

Data organization

Data are organized according to the BIDS standard in the BIDS_dataset directory. Specifications of the BIDS standard are available here.

preventad-open
|__DATS.json
|__BIDS_dataset
   |__dataset_description.json
   |__participants.json
   |__participants.tsv
   |__README
   |__sub-<candidate_id>
      |__ses-<visit_label>
            |__sub-<candidate_id>_ses-<visit_label>_scans.json
            |__sub-<candidate_id>_ses-<visit_label>_scans.tsv
                  |__anat
                        |__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.nii.gz
                        |__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.json
                        ...
                  |__asl
                        |__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.nii.gz
                        |__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.json
                        ...
                  |__dwi
                        |__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.nii.gz
                        |__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.json
                        |__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.bval
                        |__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.bvec
                        ...
                  |__fmap
                        |__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.nii.gz
                        |__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.json
                        ...
                  |__func
                        |__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.nii.gz
                        |__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>.json
                        |__ sub-<candidate_id>_ses-<visit_label>_run-<number>_<BIDS_scan_type>_events.txt
                        ...
  • DATS.json is a JSON file that describes the content of the dataset

For more information: