Agens scvi_tools

skill_id: scvi_tools name: scvi-tools description: 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. version: 1.0.0 author: K-Dense Inc. license: BSD-3-Clause license tags:

• scientific-agent-skills
• scvi-tools tools: [] permissions: network: false filesystem: false shell: false agents:
• bio_code_agent enabled: true source: scientific-agent-skills entrypoint: entry.py readme: README.md input_schema: {} output_schema: type: object metadata: upstream_repo: K-Dense-AI/scientific-agent-skills upstream_skill: scvi-tools upstream_path: scientific-skills/scvi-tools/SKILL.md upstream_frontmatter: name: scvi-tools description: 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. license: BSD-3-Clause license metadata: skill-author: K-Dense Inc.