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Tractometry pipeline

GitHub release (latest by date)

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This pipeline allows you to extract tractometry information by combining subjects's fiber bundles and diffusion MRI metrics.

Should you use this pipeline for your research, please cite the following

Cousineau, M., P-M. Jodoin, E. Garyfallidis, M-A. Cote, F.C. Morency, V. Rozanski, M. Grand'Maison, B.J. Bedell, and M. Descoteaux.
"A test-retest study on Parkinson's PPMI dataset yields statistically significant white matter fascicles."
NeuroImage: Clinical 16, 222-233 (2017) doi:10.1016/j.nicl.2017.07.020

Kurtzer GM, Sochat V, Bauer MW Singularity: Scientific containers for
mobility of compute. PLoS ONE 12(5): e0177459 (2017)
https://doi.org/10.1371/journal.pone.0177459

P. Di Tommaso, et al. Nextflow enables reproducible computational workflows.
Nature Biotechnology 35, 316–319 (2017) https://doi.org/10.1038/nbt.3820

Requirements

Singularity/Docker

If you are on Linux, we recommend using the Singularity to run tractometry_flow pipeline. If you have Apptainer (Singularity), launch your Nextflow command with: -with-singularity ABSOLUTE_PATH/scilus-1.6.0.sif

Image is available here

If you are on MacOS or Windows, we recommend using the Docker container to run tractometry_flow pipeline. Launch your Nextflow command with: -with-docker scilus/scilus:1.6.0

Usage

See USAGE or run nextflow run main.nf --help