Reproducibility
nf-neuro contains thoroughly tested and validated modules to built efficient neuroimaging pipeline ensuring reproducible results.
nf-neuro is an open-source initiative originally developed by the Sherbrooke Connectivity Imaging Lab (SCIL)
Our mission is to provide researchers with scalable, reproducible, and efficient pipelines for neuroimaging applications.
Reproducibility
nf-neuro contains thoroughly tested and validated modules to built efficient neuroimaging pipeline ensuring reproducible results.
Development guidelines
nf-neuro
is built against the nf-core
guidelines, which promotes
high coding standards and good practice.
State-of-the-art neuroimaging tools
nf-neuro
regroups multiple modules using state-of-the-art tools from
popular libraries (e.g., FSL, ANTs, scilpy, etc.).
Portability
Each components from nf-neuro have their own container (Docker or Singularity). Enabling an easy use on all architectures.
Create Your Pipeline from A to Z: Leverage our modules to build customized neuroimaging workflows.
Contribute to nf-neuro: Join our community and help advance the project.
API Documentation: Access detailed information on our modules and subworkflows and their functionalities.
Advanced tutorials: Go beyond and give superpowers to your pipeline (Add BIDS input, setup BIDS output or automatic QC)
nf-neuro is an evolving project that thrives on contributions from the community. Whether you are a researcher, developer, or enthusiast, there are multiple ways to get involved:
Report issues or suggest new features.
Contribute code, documentation, or new modules.
Engage in discussions through forums and working groups such as neurostars
By working together, we can push the boundaries of computational neuroscience and make powerful tools more accessible to all.