alterlab-pydeseq2

# PyDESeq2 ## Overview PyDESeq2 is a Python implementation of DESeq2 for differential expression analysis with bulk RNA-seq data. It supports 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 Use this skill 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" ### Does NOT Trigger | Scenario | Use Instead | |----------|-------------| | Single-cell differential expression or cluster marker genes | `alterlab-scanpy` (markers) or `alterlab-scvi-tools` (model-based DE) | | Turning FASTQ into the count matrix (salmon/kallisto/STAR quantification, tximport) | `alterlab-rnaseq-quant` | | Generic regression / GLM / mixed models on non-count data | `alterlab-statsmodels` | | Somatic or germline variant calling from sequencing reads | `alterlab-nf-core-sarek` | | Microbiome feature-table differential abundance | `alterlab-qiime2-amplicon` | ## Installation and Requirements ```bash uv pip inst...