scanpy and scvi-tools
scvi-tools builds probabilistic models for single-cell omics data analysis and integrates seamlessly with scanpy as its primary interface and data structure (AnnData), making them complements rather than competitors.
About scanpy
scverse/scanpy
Single-cell analysis in Python. Scales to >100M cells.
Provides integrated preprocessing, clustering, trajectory inference, and differential expression testing via the AnnData data structure for efficient in-memory analysis. Leverages optional Dask integration for out-of-core computation on datasets exceeding available RAM. Part of the broader scverse ecosystem, enabling interoperability with complementary single-cell analysis tools.
About scvi-tools
scverse/scvi-tools
Deep probabilistic analysis of single-cell and spatial omics data
Built on PyTorch and AnnData, scvi-tools provides modular probabilistic models for tasks like dimensionality reduction, data integration, automated annotation, doublet detection, and spatial deconvolution across single-cell and spatial omics datasets. The framework leverages PyTorch Lightning and Pyro as foundational building blocks, enabling researchers to rapidly develop and deploy custom probabilistic models with GPU acceleration and Scanpy interoperability. High-level APIs include standard save/load functions and integrate seamlessly into the broader scverse ecosystem for omics analysis.
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