Data Science & Analytics
scVI Tools
Trains and applies scvi-tools probabilistic deep generative models (scVI, scANVI, totalVI, MultiVI, PeakVI, DestVI, Solo, CellAssign, MrVI and others) on AnnData or MuData single-cell data using PyTorch. Covers batch correction, integration, cell type annotation, probabilistic differential expression, and scRNA-seq, ATAC-seq, CITE-seq, spatial and methylation data. Use when integrating batches or datasets with scVI, annotating cells with scANVI, jointly modeling RNA and protein or ATAC, deconvolving spatial spots, or testing differential expression with uncertainty. For standard preprocessing and clustering pipelines, use scanpy instead.
- Publisher / source
- KalarisLabs/research-agent-skills (found on the CSV list)
- Upstream record
- KalarisLabs/research-agent-skills
- Version
- Version 2
- Published
- Publication review
- Approved for publication
- Content fingerprint
80b300cdfbfb773ebbdf81f429b13d58082831d8331e3a8268937f7a36d617d1