scvi-tools
Run scvi-tools single-cell workflows. Use when a task asks for scVI/scANVI setup, latent embeddings, batch correction, differential expression, cell annotation, or reproducible AnnData analysis.
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Use this skill for reproducible scvi-tools analysis.
Workflow:
- Record AnnData path, organism, assay, batch keys, label keys, covariates, train/test split, and filtering choices.
- Verify Python environment, GPU/CPU route, package version, and data availability before training.
- Save preprocessing notebook, model parameters, training logs, latent embeddings, differential-expression tables, and plots.
- Check batch mixing, biological separation, marker consistency, and sensitivity to preprocessing choices.
- Attach exact commands and artifact paths to the final summary.
Keep raw counts, normalized values, and model-derived latent variables clearly separated.
- Repository
- companion-inc/feynman
- Commit
95c51d9
- Last updated
- First committed
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