Individual skill
pydeseq2
Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.
skills-imported/pydeseq2/SKILL.md
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# 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