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Fed-PyDESeq2 documentation

This package is a federated python implementation of the DESeq2 method 1 for differential expression analysis (DEA) with bulk RNA-seq data, originally in R. This federated implementation is based on Substra, an open source federated learning software.

Note that this package is actually based on (and benchmarked against) PyDESeq2 2, which is a python re-implementation of DESeq2.

Currently, available 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, without the LFC shrinkage step.

Citing this work

License

FedPyDESeq2 is released under an MIT license.

  1. Michael I Love, Wolfgang Huber, and Simon Anders. Moderated estimation of fold change and dispersion for rna-seq data with deseq2. Genome biology, 15(12):1–21, 2014. doi:10.1186/s13059-014-0550-8. ↩

  2. Boris Muzellec, Maria Telenczuk, Vincent Cabeli, and Mathieu Andreux. Pydeseq2: a python package for bulk rna-seq differential expression analysis. bioRxiv, pages 2022–12, 2022. doi:10.1101/2022.12.14.520412. ↩