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PyDESeq2 is a specialized scientific skill for Claude Code that enables researchers and bioinformaticians to perform robust differential gene expression analysis within a Python environment. It provides a comprehensive workflow for processing raw count matrices, applying Wald tests for statistical significance, and performing multiple testing corrections. The skill supports complex experimental designs, including multi-factor models to account for batch effects or covariates, and includes advanced features like apeGLM shrinkage for better effect size estimation. It is an essential tool for integrating transcriptomic data analysis into autonomous AI research pipelines or transitioning legacy R-based workflows to Python.
