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scvi-tools
Maintainer K-Dense Inc. · Last updated April 1, 2026
scvi-tools is a comprehensive Python framework for probabilistic models in single-cell genomics. Built on PyTorch and PyTorch Lightning, it provides deep generative models using variational inference for analy.
Original source
K-Dense-AI/claude-scientific-skills
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/scvi-tools
- Maintainer
- K-Dense Inc.
- License
- BSD-3-Clause license
- Last updated
- April 1, 2026
Skill Snapshot
Key Details From SKILL.md
Key Notes
- scvi-tools is a comprehensive Python framework for probabilistic models in single-cell genomics. Built on PyTorch and PyTorch Lightning, it provides deep generative models using variational inference for analyzing diverse single-cell data modalities.
- import scvi import scanpy as sc.
- adata = scvi.data.heart_cell_atlas_subsampled() sc.pp.filter_genes(adata, min_counts=3) sc.pp.highly_variable_genes(adata, n_top_genes=1200).
Source Doc
Excerpt From SKILL.md
When to Use This Skill
Use this skill when:
- Analyzing single-cell RNA-seq data (dimensionality reduction, batch correction, integration)
- Working with single-cell ATAC-seq or chromatin accessibility data
- Integrating multimodal data (CITE-seq, multiome, paired/unpaired datasets)
- Analyzing spatial transcriptomics data (deconvolution, spatial mapping)
- Performing differential expression analysis on single-cell data
- Conducting cell type annotation or transfer learning tasks
- Working with specialized single-cell modalities (methylation, cytometry, RNA velocity)
- Building custom probabilistic models for single-cell analysis
Core Capabilities
scvi-tools provides models organized by data modality:
1. Single-Cell RNA-seq Analysis
Core models for expression analysis, batch correction, and integration. See references/models-scrna-seq.md for:
- scVI: Unsupervised dimensionality reduction and batch correction
- scANVI: Semi-supervised cell type annotation and integration
- AUTOZI: Zero-inflation detection and modeling
- VeloVI: RNA velocity analysis
- contrastiveVI: Perturbation effect isolation
Use cases
- Use scvi-tools for single-cell or spatial omics analysis.
- Apply scvi-tools to clustering, integration, or trajectory workflows.
Not for
- Do not rely on this catalog entry alone for installation or maintenance details.
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