AFQ-Insight: Statistical Learning for Tractometry
Project description
AFQ-Insight Python based statistical learning for tractometry
See https://yeatmanlab.github.io/AFQ-Browser/ for documentation of the AFQ data format
This is a work in progress.
Contributing
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 = {https://www.biorxiv.org/content/early/2019/12/20/2019.12.19.882928},
eprint = {https://www.biorxiv.org/content/early/2019/12/20/2019.12.19.882928.full.pdf},
journal = {bioRxiv}
}
Acknowledgements
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).
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