scvi-tools

SKILL.md

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.

Single-Cell RNA-seq Analysis Core models for expression analysis, batch correction, and integration. See references/models-scrna-seq.md for:

Chromatin Accessibility (ATAC-seq) Models for analyzing single-cell chromatin data. See references/models-atac-seq.md for:

This skill should be used when working with single-cell omics data analysis using scvi-tools, including scRNA-seq, scATAC-seq, CITE-seq, spatial transcriptomics, and other single-cell modalities. Use this skill for probabilistic modeling, batch correction, dimensionality reduction, differential expression, cell type annotation, multimodal integration, and spatial analysis tasks. Source: ovachiever/droid-tings.

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