PyDESeq2#
PyDESeq2 is a Python implementation of the DESeq2 method [LHA14] for differential expression analysis with bulk RNA-seq data, originally written in R.
It works on AnnData objects and is part of the scverse ecosystem.
Because PyDESeq2 is a reimplementation from scratch, you may see differences in retrieved values or available features. Current features broadly correspond to the default settings of DESeq2 (v1.34.0) for single-factor and multi-factor analysis, with categorical or continuous factors, using Wald tests, plus an optional apeGLM log fold-change shrinkage step [ZIL19]. If there is a feature you would like to see, open an issue on GitHub.
Install PyDESeq2 with pip or conda.
Runnable examples, from a minimal pipeline to a step-by-step walkthrough.
Every class and function, with its parameters and return values.
What DESeq2 does, what PyDESeq2 covers, and where the two differ.
Set up a development environment and open a pull request.
Read the source, report a bug, or open a pull request.
NumFOCUS#
PyDESeq2 is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS. If you like scverse® and want to support our mission, please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.