scvi-tools (single-cell variational inference tools) is a package for probabilistic modeling of single-cell omics data, built on top of PyTorch and AnnData. The package hosts implementations of models that perform a wide range of single-cell data analysis tasks, as well as the building blocks to rapidly prototype new probabilstic models.
scvi-tools can be installed with
To leverage a GPU for inference, a version of PyTorch that supports your GPU will need to be installed separately.
scvi-tools hosts implementations of the following models:
- scVI for analysis of single-cell RNA-seq data, as well as its improved differential expression framework.
- scANVI for cell annotation of scRNA-seq data using semi-labeled examples.
- LDVAE for an interpretable linear factor model version of scVI.
- totalVI for analysis of CITE-seq data.
- Steroscope for deconvolution of spatial transcriptomics data.
- gimVI for imputation of missing genes in spatial transcriptomics from scRNA-seq data.