PyDESeq2: a python package for bulk RNA-seq differential expression analysis.
Journal
Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944
Informations de publication
Date de publication:
02 09 2023
02 09 2023
Historique:
received:
14
12
2022
revised:
03
08
2023
accepted:
04
09
2023
medline:
18
9
2023
pubmed:
5
9
2023
entrez:
5
9
2023
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 37669147
pii: 7260507
doi: 10.1093/bioinformatics/btad547
pmc: PMC10502239
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© The Author(s) 2023. Published by Oxford University Press.
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