PyDESeq2: a python package for bulk RNA-seq differential expression analysis

By Boris Muzellec, Maria Teleńczuk, Vincent Cabeli, Mathieu Andreux. bioRxiv, 2022

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Summary We present PyDESeq2, a python implementation of the DESeq2 workflow for differential expression analysis on bulk RNA-seq data. This implementation achieves better precision, allows speed improvements on large datasets, as shown in experiments on TCGA data, and can be more easily interfaced with modern python-based data science tools. Availability and Implementation PyDESeq2 is released as an open-source software under the MIT license. The source code is available on GitHub at https://github.com/owkin/PyDESeq2. Contact boris.muzellec@owkin.com

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/9c4d7768b5c2e10fe5e39739d8a55589a3d1d3bc