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AFQ-Insight: Statistical Learning for Tractometry

Project description

AFQ-Insight Python based statistical learning for tractometry

Build Status Coverage Status Code style: black License DOI

See for documentation of the AFQ data format

This is a work in progress.


We love contributions! AFQ-Insight is open source, built on open source, and we'd love to have you hang out in our community.

We have developed some guidelines for contributing to AFQ-Insight.

Citing AFQ-Insight

If you use AFQ-Insight in a scientific publication, please see cite us:

Richie-Halford, A., Yeatman, J., Simon, N., and Rokem, A. Multidimensional analysis and detection of informative features in diffusion MRI measurements of human white matter. DOI:10.1101/2019.12.19.882928

@article {Richie-Halford2019.12.19.882928,
	author = {{R}ichie-{H}alford, {A}dam and {Y}eatman, {J}ason and {S}imon, {N}oah and {R}okem, {A}riel},
	title = {{M}ultidimensional analysis and detection of informative features in diffusion {MRI} measurements of human white matter},
	elocation-id = {2019.12.19.882928},
	year = {2019},
	doi = {10.1101/2019.12.19.882928},
	publisher = {Cold Spring Harbor Laboratory},
	URL = {},
	eprint = {},
	journal = {bioRxiv}


AFQ-Insight development is 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, as well as NIMH BRAIN Initiative grant 1RF1MH121868-01 to Ariel Rokem (University of Washington).

Project details

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