Metadata-Version: 2.1
Name: sopnmf
Version: 0.0.4
Summary: Stochastic Orthogonal Projective Non-negative Matrix Factorization
Home-page: https://github.com/anbai106/SOPNMF
Author: junhao.wen
Author-email: junhao.wen89@email.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE

<h1 align="center">
  <a href="https://anbai106.github.io/SOPNMF/">
    <img src="https://anbai106.github.io/SOPNMF/images/sopnmf.png" alt="SOPNMF Logo" width="120" height="120">
  </a>
  <br/>
  SOPNMF
</h1>

<p align="center"><strong>Stochastic orthogonally projective non-negative matrix factorization</strong></p>

<p align="center">
  <a href="https://anbai106.github.io/SOPNMF/">Documentation</a>
</p>

## About the project
**SOPNMF** is the python implementation of the Matlab version of Orthogonal Projective Non-negative Matrix Factorization: [brainparts](https://github.com/asotiras/brainparts), and its stochastic extension.

> :warning: **The documentation of this software is currently under development**

## Citing this work
> Junhao, W.E.N., Abdulkadir, A., Satterthwaite, T.D., Robert-Fitzgerald, T., Chen, J., Schnack, H., Zanetti, M., Meisenzahl, E., Busatto, G., Crespo-Facorro, B. and Pantelis, C., 2022. **Novel genomic loci and pathways influence patterns of structural covariance in the human brain**. medRxiv. - [In review](https://www.medrxiv.org/content/10.1101/2022.07.20.22277727v1)

> Sotiras, A., Resnick, S.M. and Davatzikos, C., 2015. **Finding imaging patterns of structural covariance via non-negative matrix factorization**. Neuroimage, 108, pp.1-16. [doi:10.1016/j.neuroimage.2014.11.045](https://www.sciencedirect.com/science/article/pii/S1053811914009756?via%3Dihub)

## Publications around SOPNMF
> Wen, J., Varol, E., Sotiras, A., Yang, Z., Chand, G.B., Erus, G., Shou, H., Abdulkadir, A., Hwang, G., Dwyer, D.B. and Pigoni, A., 2022. Multi-scale semi-supervised clustering of brain images: deriving disease subtypes. Medical Image Analysis, 75, p.102304. - [Link](https://scholar.google.com/citations?view_op=view_citation&hl=en&user=4Wq_FukAAAAJ&sortby=pubdate&citation_for_view=4Wq_FukAAAAJ:9ZlFYXVOiuMC)


