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

2023; Oxford University Press; Volume: 39; Issue: 9 Linguagem: Inglês

10.1093/bioinformatics/btad547

1367-4811

Boris Muzellec, Maria Teleńczuk, Vincent Cabeli, Mathieu Andreux,

Single-cell and spatial transcriptomics

We present PyDESeq2, a python implementation of the DESeq2 workflow for differential expression analysis on bulk RNA-seq data. This re-implementation yields similar, but not identical, results: it achieves higher model likelihood, 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.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 and documented at https://pydeseq2.readthedocs.io. PyDESeq2 is part of the scverse ecosystem.