A single skill that provides comprehensive access to deep learning-based single-cell analysis using scvi-tools and the scVerse ecosystem, covering batch integration (scVI, scArches), cell type annotation (SCANVI, CellAssign), spatial transcriptomics deconvolution (DestVI, Tangram, cell2location, Stereoscope), chromatin accessibility analysis (PeakVI, scBasset), multimodal data integration (TotalVI for CITE-seq, MultiVI for RNA+ATAC), and perturbation analysis (contrastiveVI). Each skill provides step-by-step workflows, parameter tuning guidance, and troubleshooting for its respective scvi-tools model.
This skill is designed for scientists analyzing single-cell, including spatial, epigenetic and scRNA, data who want to leverage deep learning methods from scvi-tools without needing to read through extensive documentation—particularly useful for researchers working with multi-batch experiments, multimodal assays (CITE-seq, multiome), spatial transcriptomics, or scATAC-seq who need guidance on model selection, parameter tuning, and best practices.
Command
/plugin marketplace add anthropics/life-sciences
/plugin install scvi-tools@life-sciences
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