Abstract
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.
Cite
CITATION STYLE
APA
Muzellec, B., Teleńczuk, M., Cabeli, V., & Andreux, M. (2023). PyDESeq2: a python package for bulk RNA-seq differential expression analysis. Bioinformatics, 39(9). https://doi.org/10.1093/bioinformatics/btad547
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