pydeseq2

SKILL.md

PyDESeq2

Overview

PyDESeq2 is a Python implementation of DESeq2 for differential expression analysis with bulk RNA-seq data. Design and execute complete workflows from data loading through result interpretation, including single-factor and multi-factor designs, Wald tests with multiple testing correction, optional apeGLM shrinkage, and integration with pandas and AnnData.

When to Use This Skill

This skill should be used when:

Analyzing bulk RNA-seq count data for differential expression

Comparing gene expression between experimental conditions (e.g., treated vs control)

Performing multi-factor designs accounting for batch effects or covariates

Converting R-based DESeq2 workflows to Python

Integrating differential expression analysis into Python-based pipelines

Users mention "DESeq2", "differential expression", "RNA-seq analysis", or "PyDESeq2"

Quick Start Workflow

For users who want to perform a standard differential expression analysis: