Metadata-Version: 2.1
Name: phosphodisco
Version: 0.0.2
Summary: A package for the discovery of co-regulated phosphorylation modules
Home-page: https://github.com/ruggleslab/phosphodisco
Author: Tobias Schraink, Ruggles Lab
Author-email: Tobias Schraink <tschraink@gmail.com>
License: MIT License
        
        Copyright (c) 2019 Ruggles Lab
        
        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
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        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
        copies or substantial portions of the Software.
        
        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
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
Project-URL: Homepage, https://github.com/ruggleslab/phosphodisco
Project-URL: Bug Tracker, https://github.com/ruggleslab/phosphodisco/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE

# PhosphoDisco (PhDc)
A python package for finding co-regulated phospho sites from phosphoproteomics and proteomics data.   


## Description
PhDc uses optimized clustering to find co-regulated phosphosite modules. Then, PhDc uses protein and phosphoprotein abundance data from kinases and phosphatases to nominate module regulators. It can also use sample annotation data to identify modules significantly correlated with clinical variables. 

See the docs at [https://github.com/ruggleslab/phosphodisco](https://github.com/ruggleslab/phosphodisco)
