TRR289 MEGA Dataset

ℹ️ Information

This repository is the Github sibling of the corresponding DataLad dataset, i.e. it does not contain the data itself. The GitHub sibling, nevertheless, provides insights into the general data structure (directory tree, filenames) and serves as a starting point to download, share and discuss the dataset. Data follow the BIDS Extension proposal 35 (BEP035), BIDS-MEGA format and includes a collection of dataset from the TRR289 project for mega-analytic purposes. The single BIDS datasets contained at the mega-analysis level are stored in Coscine and can't be downloaded without the dataset specific secret token. Token is available at project Z03 for members of TRR289 and collaborators upon reasonable request.

See dataset_description.json for project related meta-data and bids_mapper.json for mega-analysis level meta-data.

⬇️ How to download dataset

1. Install it with DataLad based on the github handle

This does not download the actual data, only the gin-annex "skeleton".

datalad install -s git@github.com:pni-data/<dataset_name>.git <dataset_name>

2. Change to the dataset directory and download the file(s) you want

You can selectively download what you need (e.g. derivatives only).

cd <dataset_name>
datalad get <path/to/file*>

For an explanation about how to get data from the single TRR289 datasets see our documentation.

Comments added by the SFB289 Z03 project coordinators

General Comments

ToDo link detailed information about the dataset. eg: The sub-datasets were acquired by the teams of the TRR/SFB289. The whole mega-analysis dataset includes ?? subjects with the common sequences within the SFB289 project, namely a high resolution T1w, resting state fMRI, 133 direction multi shell DWI, and 2 fieldmaps for the functional data and one fieldmap for the DWI (reversed field encoding direction). An additional reference image of the resting state fMRI is included without multiband factor.

ToDo: Questionnaires data are also acquired and can be found in the ... folder.

The proposal can be found here: ToDo link

The BIDS conversion was done with heudiconv by the Z03 project coordinators.

Defacing

Defacing was done by the Z03 coordinator. Pydeface was used on all anatomical images to ensure de-identification of subjects. The code can be found at https://github.com/poldracklab/pydeface

Known Issues

N/A

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bids-validator

The bids-validator doesn't currently support the BIDS-MEGA format.