scvi-tools

Deep generative models for single-cell omics. Use when you need probabilistic batch correction (scVI), transfer learning, differential expression with uncertainty, or multi-modal integration (TOTALVI, MultiVI). Best for advanced modeling, batch effects, multimodal data. For standard analysis pipelines use scanpy.

1.14x

Quality

85%

Does it follow best practices?

Impact

95%

1.14x

Average score across 3 eval scenarios

Securityby

Passed

No findings from the security scan

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Run	Type	Date	Status
baseline vs usage-spec With / without context 7 months ago Completed	With / without context	7 months ago	Completed

Eval run

019cb98b-6596-71b9-b388-11f5fc4240f1

Run 7 months ago

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Repository: wu-yc/LabClaw
Path: skills/bio/scvi-tools/SKILL.md
Commit: df37802

Evaluated: 7 months ago
Agent: Claude Code
Model: Claude Sonnet 4.6

Table of Contents

Multi-Donor scRNA-seq Integration Pipeline Identifying Disease-Associated Gene Expression Changes in T Cells Automated Cell Type Annotation for a New Patient Cohort

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