ModuleRefinement is a package for gene co-expression module refinement. This package provides an API for reproducing the results in the gene co-expression module refinement paper.

See examples/small_example.ipynb for a notebook that details simple usage of ModuleRefinement along with PyWGCNA.

If you like this work, please consider citing us

@article{mankovich2023module,
  title={Module representatives for refining gene co-expression modules},
  author={Mankovich, Nathan and Andrews-Polymenis, Helene and Threadgill, David and Kirby, Michael},
  journal={Physical Biology},
  volume={20},
  number={4},
  pages={045001},
  year={2023},
  publisher={IOP Publishing}
}

See requirements.txt. ModuleRefinement was built with Python 3.8.8.

1. Initialize conda environment

   conda create --name module_refinement python=3.8.8
   conda activate module_refinement
   

2. Install requirements

   pip install -r requirements.txt
   

3. Install ModuleRefinement package

   python -m pip install --index-url https://test.pypi.org/simple/ --no-deps ModuleRefinement==0.0.14
   

4. Open ./examples/small_example.ipynb and run it within themodule_refinement environment.

small_example.ipynb shows how to compute:

• WGCNA modules
• Refined modules using subspace LBG clustering
• Relative gain in GO signiciance
• Relative gain in classification BSR

Nathan Mankovich: [email protected]

• 0.8
  • Initial functional release

See the LICENSE.md file for details

Big thank you to EricStern for his help packaging the repository and ensuring reproducibility. Another thanks to EricKehoe for his work on the code base for Pathway Expression Analysis which was used to run some of these examples.