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- Title
PyDESeq2: a python package for bulk RNA-seq differential expression analysis.
- Authors
Muzellec, Boris; Teleńczuk, Maria; Cabeli, Vincent; Andreux, Mathieu
- Abstract
Summary 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. 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 and documented at https://pydeseq2.readthedocs.io. PyDESeq2 is part of the scverse ecosystem.
- Subjects
MASSACHUSETTS Institute of Technology; RNA sequencing; PYTHON programming language; SOURCE code; DATA science; PYTHONS; WORKFLOW
- Publication
Bioinformatics, 2023, Vol 39, Issue 9, p1
- ISSN
1367-4803
- Publication type
Article
- DOI
10.1093/bioinformatics/btad547