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name: dea-workflows description: "Run practical PyDESeq2 differential expression workflows with DeseqDataSet and DeseqStats." disable-model-invocation: true metadata: disco-role: operating license: MIT

PyDESeq2 DEA Workflows

Use this sub-skill when an agent needs to run an end-to-end PyDESeq2 differential expression analysis after count and metadata inputs are already validated.

Route First

• For CSV loading, count orientation, metadata/index alignment, AnnData setup, and input validity failures, use ../data-io-validation/SKILL.md.
• For p-value interpretation, result columns, alternative hypotheses, LFC shrinkage details, and MA plots, use ../statistics-and-results/SKILL.md.
• For stepwise fitting internals, normalization helpers, VST, and advanced model-state inspection, use ../model-fitting-internals/SKILL.md.

Standard Flow

1. Start from a samples-by-genes raw count table and metadata indexed by the same sample IDs.
2. Bound parallelism explicitly with DefaultInference(n_cpus=1) or another user-approved CPU count.
3. Build DeseqDataSet(counts=..., metadata=..., design="~condition", inference=..., refit_cooks=True).
4. Run dds.deseq2() once to fit size factors, dispersions, LFCs, Cook's distances, and optional outlier refit.
5. Create one or more DeseqStats(dds, contrast=...) objects from the fitted dataset and call summary().
6. Export stats.results_df to CSV when the user wants a table; export dds.to_picklable_anndata() only when the fitted object itself is needed.

Quick Commands

• From this sub-skill directory, run the bundled script on PyDESeq2 synthetic example data: python scripts/run_synthetic_dea.py --n-cpus 1 --quiet.
• Save a results table: python scripts/run_synthetic_dea.py --output-csv results.csv --overwrite --quiet.
• Try a multi-factor design on PyDESeq2 synthetic example data: python scripts/run_synthetic_dea.py --design "~group + condition" --contrast condition B A --filter-column group --quiet.

Reference Map

• references/workflows.md gives copyable single-factor, multi-factor, continuous-factor, low-memory, outlier-refit, and export skeletons.
• references/api-reference.md summarizes the PyDESeq2 0.5.4 workflow APIs and object handoff contract.
• references/troubleshooting.md covers common end-to-end DEA workflow failures and safe fixes.