Methods - pyDESeq2

PyDeSeq2

DESeq2 is a widely utilized R-package that facilitates RNA-Seq data analysis. In our project, we utilized PyDESeq2, a Python interface to DESeq2, introduced by Muzullec et al. (2023). PyDESeq2 follows the differential expression analysis (DEA) method outlined by Love et al. (2014), which models raw count data using a negative binomial distribution. Initially, dispersion parameters are determined for each gene using a negative binomial GLM. These parameters are then adjusted towards a global trend curve, enabling estimation of gene-specific log-fold changes (LFC) and Wald tests for differential expression between experimental cohorts. 

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