cohort-creator 0.3.0

Creates a neuroimaging cohort by aggregating data across datasets.

Cohort creator

TL;DR

Creates a neuroimaging cohort by aggregating data across datasets.

Command line tool to:

• install a set of BIDS datalad datasets,
• get the data for a set of participants,
• copy the data to a new directory structure to create a "cohort".

It takes 2 files as input that should list:

• datasets to be included in the cohort
• subject in each dataset to be included in the cohort

Both of those files can be generated by the neurobagel query tool.

For examples of inputs TSV files see this page.

It outputs the cohort following the recommendations from the BIDS extension proposal 35.

Requirements

Operating system

It is recommended to use this package on a linux / Mac OS.

If you are on Windows, try using WSL (Windows Subsystem for Linux) to run this package: windows does not handle symbolic links well, and this package relies on symlinks. If you decided to go ahead anyway make sure you have got a LOT of disk space available.

More information here

Python dependencies

Make sure you have the following installed:

• datalad and its dependencies:

  • if you are have anaconda / conda, it should be 'just' a matter of running

    conda install -c conda-forge datalad
    

  • But check the installation instructions for more details.

Other dependencies are listed in the pyproject.toml file.

Installation

pip install cohort_creator

Installation from source

git clone https://github.com/neurodatascience/cohort_creator.git
cd cohort_creator
pip install .

Limitations

Cohorts can only be created by aggregating data from open BIDS datasets curated with datalad.

Dataset types

Only possible to get data from:

• raw
• mriqc
• fmriprep

Not yet possible to get freesurfer data via the cohort creator, though the data is available in the sourcedata folder of the fmriprep datasets.

Blind spots

It may be possible that that some metadata files (JSON, TSV) are not accessed over correctly if they are not in the root of the dataset or the same folder as the data file.

Contributors ✨

Thanks goes to these wonderful people (emoji key):

Michelle Wang 🐛 🤔 📓

Remi Gau ⚠️ 🚧 📖 🐛 💻

This project follows the all-contributors specification. Contributions of any kind welcome!