Metadata-Version: 2.3
Name: gnatpy
Version: 0.2.0
Summary: Analyze Rank Entropy in Python
Keywords: entropy,rank,gene,bioinformatics
Author: Braden Griebel
Author-email: Braden Griebel <bgriebel@uw.edu>
License: MIT License
         
         Copyright (c) 2026 Braden Griebel
         
         Permission is hereby granted, free of charge, to any person obtaining a copy
         of this software and associated documentation files (the "Software"), to deal
         in the Software without restriction, including without limitation the rights
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         copies of the Software, and to permit persons to whom the Software is
         furnished to do so, subject to the following conditions:
         
         The above copyright notice and this permission notice shall be included in all
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         THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
         IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
         FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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Requires-Dist: joblib>=1.4.2
Requires-Dist: numpy>=2.0.0
Requires-Dist: pandas>=2.2.0
Requires-Dist: scikit-learn>=1.6.1
Requires-Dist: scipy>=1.12.0
Requires-Python: >=3.9
Project-URL: Homepage, https://github.com/Ma-Lab-Seattle-Childrens-CGIDR/gnatpy
Project-URL: Repository, https://github.com/Ma-Lab-Seattle-Childrens-CGIDR/gnatpy
Project-URL: Documentation, https://gnatpy.readthedocs.io/en/latest/
Project-URL: Issues, https://github.com/Ma-Lab-Seattle-Childrens-CGIDR/gnatpy/issues
Project-URL: Changelog, https://github.com/Ma-Lab-Seattle-Childrens-CGIDR/gnatpy/blob/main/CHANGELOG.md
Description-Content-Type: text/markdown

# GNATpy

<img src="gnatpy_logo.png" alt="GNATpy Logo" width="200"/>

Welcome to GNATpy, the Gene Network rAnk enTropy python package!
This package includes several methods for analyzing the rank entropy
of a gene network between two different groups of samples.

## Usage

GNATpy can be installed from PyPI with

```{bash}
pip install gnatpy
```

See the [documentation](https://gnatpy.readthedocs.io/en/stable/) for more information

## Licensing

The code for GNATpy is licensed under an MIT license, see the LICENSE file for more information.
The GNATpy logo is licensed under a [CC0](https://creativecommons.org/publicdomain/zero/1.0/) license.

## References

### DIRAC

- Eddy, J. A., Hood, L., Price, N. D., & Geman, D. (2010). Identifying Tightly Regulated and Variably Expressed Networks by Differential Rank Conservation (DIRAC). PLoS Computational Biology, 6(5), e1000792. [https://doi.org/10.1371/journal.pcbi.1000792](https://doi.org/10.1371/journal.pcbi.1000792)
