PyDESeq2
Runs bulk RNA-seq differential expression in Python instead of R.
Install
Ships scriptsgh skill install K-Dense-AI/scientific-agent-skills pydeseq2
Differential expression on bulk RNA-seq counts, multi-factor designs with batch or covariate terms, or porting a DESeq2 workflow from R.
- Author
- K-Dense Inc.
- License
- MIT
Follows the DESeq2 procedure end to end through the PyDESeq2 package: count filtering, dispersion estimation, Wald tests, Benjamini-Hochberg correction and optional apeGLM shrinkage. Multi-factor formulaic designs are covered, so a batch term or covariate sits inside the model rather than being cleaned out beforehand. Every example writes the reference level and the contrast explicitly, which is where a workflow ported from R most often flips sign. One bundled script runs the whole analysis from a counts table and a sample metadata table.
Similar skills
Scanpy
SkillStandard single-cell RNA-seq workflow from QC through clustering and marker genes.
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SkillChooses and lays out a study design before any data is collected.
statsmodels
SkillRegression, GLM and time series models with the full inference output.
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