概要
The PyDESeq2 skill enables automated and high-precision differential gene expression (DGE) analysis within Python-based bioinformatics pipelines. It implements the robust DESeq2 statistical framework, allowing researchers to model count data, estimate dispersions, and perform Wald tests with multiple testing corrections. This skill is particularly useful for identifying significant genetic markers across experimental conditions while accounting for complex variables like batch effects and covariates, making it a vital tool for transcriptomics and genomic data science.
