This app will convert the Freesurfer stats files created during recon-all into a user-friendly, tidy format csv for downstream analyses. This app uses an open source package called 'FreesurferStats' to do the conversion for us. This app will output a parc-stats datatype containing the information for each parcel for the chosen Freesurfer parcellation.
- Brad Caron ([email protected])
- Soichi Hayashi ([email protected])
brainlife.io is publicly funded and for the sustainability of the project it is helpful to Acknowledge the use of the platform. We kindly ask that you acknowledge the funding below in your publications and code reusing this code.
We kindly ask that you cite the following articles when publishing papers and code using this code.
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Avesani, P., McPherson, B., Hayashi, S. et al. The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Sci Data 6, 69 (2019). https://doi.org/10.1038/s41597-019-0073-y
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Dale, A.M., Fischl, B., Sereno, M.I., 1999. Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage 9, 179-194.
You can submit this App online at https://doi.org/10.25663/brainlife.app.272 via the 'Execute' tab.
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git clone this repo
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Inside the cloned directory, create
config.json
with something like the following content with paths to your input files.
{
"freesurfer": "/input/freesurfer/output",
"parcellation": "aparc"
}
You can download sample datasets from Brainlife using Brainlife CLI.
npm install -g brainlife
bl login
mkdir input
bl dataset download
- Launch the App by executing 'main'
./main
The main output of this App is a parc-stats datatype containing a csv file containing data for each measure and parcel within the chosen Freesurfer parcellation.
The secondary output of this app is product.json
. This file allows web interfaces, DB and API calls on the results of the processing.
This App only requires singularity to run. If you don't have singularity, you will need to install following dependencies.
- Freesurfer: https://surfer.nmr.mgh.harvard.edu/
- FSL: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki
- python3: https://www.python.org/downloads/
- pandas: https://pandas.pydata.org/
- numpy: https://numpy.org/
- matlab: https://www.mathworks.com/products/matlab.html
- vistasoft: https://github.com/vistalab/vistasoft
- jsonlab: https://github.com/fangq/jsonlab
- wma_tools: https://github.com/DanNBullock/wma_tools
- Freesurfer Stats: https://github.com/fphammerle/freesurfer-stats