AFQ-Insight: Statistical learning for tractometry data

AFQ-Insight is a Python library for statistical learning of tractometry data.

Tractometry assesses the tissue properties of the major white matter connections between different brain regions. AFQ-Insight inter-operates with the results of tractometry produced by the pyAFQ software library. However, you can also use the output of other tractometry pipelines if you convert them into the format produced by pyAFQ.

Getting started

See the getting started page for installation and basic usage instructions.

User Guide

See the user guide for further information on how to use AFQ-Insight.

API Documentation

See the API Documentation for detailed documentation of the API.

Examples

And look at the example gallery for a set of introductory examples.

Citing AFQ-Insight

If you use AFQ-Insight in a scientific publication, we would appreciate citations. Please see our citation instructions for the latest reference and a bibtex entry.

Acknowledgements

AFQ-Insight development was supported through a grant from the Gordon and Betty Moore Foundation and from the Alfred P. Sloan Foundation to the University of Washington eScience Institute, NIH Collaborative Research in Computational Neuroscience grant R01EB027585-01 through the National Institute of Biomedical Imaging and Bioengineering to Eleftherios Garyfallidis (Indiana University) and Ariel Rokem (University of Washington) and NIH grant RF1MH121868 (PIs: Ariel Rokem, Jason Yeatman and Noah Simon) from the National Institute of Mental Health and the BRAIN Initiative Informatics program.