Nipoppy

Nipoppy is a lightweight framework for standardized organization and processing of neuroimaging-clinical datasets. Its goal is to help users adopt the FAIR principles and improve the reproducibility of studies.

The framework includes three components:

• A protocol for going from raw study data to analysis-ready features.
• A specification for dataset organization that extends the Brain Imaging Data Structure (BIDS) standard by providing additional guidelines for tabular (e.g., phenotypic) data and imaging derivatives.
• A command-line interface and Python package that provide user-friendly tools for applying the framework. The tools build upon existing technologies such as the Apptainer container platform and the Boutiques descriptor framework. Several existing containerized pipelines are supported out-of-the-box, and new pipelines can be added easily by the user.

Project Author(s)

Michelle Wang; Nikhil Bhagwat; Mathieu Dugré; Rémi Gau; Brent McPherson; Nipoppy contributors; Jean-Baptiste Poline

Project Links

https://nipoppy.readthedocs.io/en/stable/

This post was automatically generated by Michelle Wang