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

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 show...

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Veröffentlicht in:Bioinformatics (Oxford, England) Jg. 39; H. 9
Hauptverfasser: Muzellec, Boris, Teleńczuk, Maria, Cabeli, Vincent, Andreux, Mathieu
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford University Press 02.09.2023
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ISSN:1367-4811, 1367-4803, 1367-4811
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Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
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content type line 23
ISSN:1367-4811
1367-4803
1367-4811
DOI:10.1093/bioinformatics/btad547