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scvi-tools Skill

AI Agent SkillPythonOpen source

Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics decon Published by anthropics in life-sciences.

What is scvi-tools Skill?

Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics decon Published by anthropics in life-sciences. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.

Trust signal
95/100
Maintenance signal
90/100
Adoption signal
68/100

Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.

Key capabilities

  • Includes SKILL.md support
  • Reusable instructions support
  • Data analysis
  • Data analysis use cases

Technical details

Copy skill directory
  • Install or run with Copy skill directory

When to use scvi-tools Skill

  • Use it for data analysis.

Built with

PythonCopy skill directory

Editorial notes

Source

  • Creator: anthropics
  • Repository: anthropics/life-sciences
  • Skill file: scvi-tools/SKILL.md

What it does

Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics decon

Skill instructions

scvi-tools Deep Learning Skill This skill provides guidance for deep learning-based single-cell analysis using scvi-tools, the leading framework for probabilistic models in single-cell genomics. How to Use This Skill 1. Identify the appropriate workflow from the model/workflow tables below 2. Read the corresponding reference file for detailed steps and code 3. Use scripts in scripts/ to avoid rewriting common code 4. For installation or GPU issues, consult references/environmentsetup.md 5. For debugging, consult references/troubleshooting.md When to Use This Skill - When scvi-tools, scVI, scANVI, or related models are mentioned - When deep learning-based batch correction or integration is needed - When working with multi-modal data (CITE-seq, multiome) - When reference mapping or label transfer is required - When analyzing ATAC-seq or spatial transcriptomics data - When learning latent representations of single-cell data Model Selection Guide | Data Type | Model | Primary Use Case | |-

Explore related resources

Frequently asked questions

What is scvi-tools?

scvi-tools is a open-source AI agent skill with Copy skill directory. Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq.

Who is scvi-tools best for?

scvi-tools is best for reusing agent instructions, scripts, and references, data analysis workflows.

How do I install scvi-tools?

Install or run scvi-tools using Copy skill directory. Check scvi-tools for the latest setup command.

Is scvi-tools actively maintained?

scvi-tools may need a closer maintenance check before production use.

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Stars
525
Forks
101
Last commit
3 months ago
Repository age
9 months
License
Unknown

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