Model single-cell omics data with scvi-tools for batch-corrected analysis.
npx skills add https://github.com/jackspace/ClaudeSkillz --skill scvi-tools
Please help me install this Agent Skill. Skill: scvi-tools Source: https://github.com/jackspace/ClaudeSkillz/tree/main/skills/scientific-pkg-scvi-tools Command: npx skills add https://github.com/jackspace/ClaudeSkillz --skill scvi-tools
This Skill helps you analyze single-cell omics data using scvi-tools, enabling probabilistic modeling, batch correction, and multimodal integration across modalities including scRNA-seq, scATAC-seq, CITE-seq, and spatial transcriptomics.
Install scvi-tools, prepare an AnnData object, configure the SCVI model, train, and extract latent representations for downstream analysis.
High-intent search queries and answers about installing and using this skill.
Batch correction in scvi-tools learns batch-aware latent representations using probabilistic models like SCVI, enabling cross-dataset integration by accounting for technical variation while preserving biological signal across scRNA-seq experiments.
Yes. scvi-tools supports multimodal integration across scRNA-seq, scATAC-seq, CITE-seq, and spatial transcriptomics by building unified probabilistic models that learn shared latent representations across modalities.
Load data into AnnData, configure and train a SCVI model, extract latent representations for dimensionality reduction, then use probabilistic differential expression and annotation tools to identify cell types across your dataset.
Yes. scvi-tools includes GPU acceleration support, enabling efficient probabilistic modeling and training on large-scale single-cell datasets when GPUs are available in your environment.
Yes. scvi-tools includes spatial analysis capabilities, allowing you to perform spatial mapping, integrate spatial transcriptomics with other modalities, and extract spatially-aware probabilistic representations.
scvi-tools accepts raw-count data in AnnData format, the standard Python framework for single-cell omics. It handles scRNA-seq, scATAC-seq, CITE-seq, and spatial data through a unified AnnData-compatible API.
TianGzlabAutomate cell type annotation for single-cell omics data using marker genes, CellTypist, SingleR, or scmap.
tassiovaleAnalyze single-cell RNA-seq data with scvi-tools deep generative models.
tony-zhelonkinPerform unsupervised integration and batch correction for scRNA-seq data using scVI.
Victory-HugoRun scvi-tools deep generative models on single-cell RNA sequencing data.
