scvi-tools
De la autor
Deep generative models for single-cell omics. Use when you need probabilistic batch correction (scVI), transfer learning, differential expression with uncertainty, or multi-modal integration (TOTALVI, MultiVI). Best for advanced modeling, batch effects, multimodal data. For standard analysis pipelines use scanpy.
Instalare
npx skills add BioTender-max/awesome-bio-agent-skills --skill scvi-tools -a claude-code
Se instalează în .claude/skills/scvi-tools/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Fără descărcare: licența acestui skill (Personalizată sau neclară) nu ne permite să-i redistribuim fișierele. Comenzile de instalare le iau direct de pe GitHub.
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De ce 74
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Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- alterlab-scvi-toolsAlterLab-IEU/AlterLab-Academic-SkillsTrain deep generative models for single-cell omics with scvi-tools — probabilistic batch correction and integration (scVI), reference-mapping transfer learning (scArches), differential expression with uncertainty, and multimodal models (totalVI for CITE-seq, MultiVI for multiome). Use when correcting batch effects, integrating multimodal data, or doing advanced probabilistic single-cell modeling — for standard analysis pipelines use scanpy. Part of the AlterLab Academic Skills suite.Altele★ 85
- scvi-tools-single-celljaechang-hits/SciAgent-SkillsDeep generative models for single-cell omics: probabilistic batch correction (scVI), semi-supervised annotation (scANVI), CITE-seq RNA+protein (totalVI), transfer learning (scARCHES), and DE with uncertainty. Unified setup→train→extract API on AnnData. Use harmony-batch-correction for fast linear correction without deep learning; muon for multi-modal MuData workflows.Știință★ 385
- scanpyK-Dense-AI/scientific-agent-skillsPerforms Scanpy single-cell RNA-seq QC, normalization, HVG selection, PCA/UMAP/t-SNE, clustering, exploratory marker ranking, pseudobulk preparation, visualization, and Seurat or SingleCellExperiment RDS conversion to h5ad. Applies to established exploratory scRNA-seq workflows with explicit count and expression provenance; complementary skills cover scvi-tools models and AnnData format details.Marketing★ 56.2K
- multimodal-omics-integrationjaechang-hits/SciAgent-SkillsMultimodal and multi-section integration for spatial and single-cell omics: totalVI joint RNA + protein (Visium CytAssist Gene and Protein, CITE-seq), MultiVI joint RNA + ATAC (10x Multiome, spatial ATAC-RNA), BBKNN integration of several tissue sections, scanpy ingest label transfer between sections, and gene signature scores mapped on tissue. Outputs joint latent spaces, denoised protein maps, integrated clusters, transferred labels. For dissociated CITE-seq and scVI/scANVI use scvi-tools-single-cell; for MOFA+ factor analysis use mofaplus-multi-omics or muon-multiomics-singlecell; for Harmony use harmony-batch-correction.Știință★ 385
- scrna-seq-pipelineawslabs/hcls-agent-skillsScanpy-based single-cell RNA-seq analysis pipeline covering loading (10X, h5ad), QC, normalization, HVG selection, PCA/UMAP, Leiden clustering, differential expression, and batch correction (Harmony, scVI). Use when the user mentions single-cell, scRNA-seq, Scanpy, AnnData, UMAP, clustering, 10X, h5ad, leiden, highly variable genes, Harmony, scVI, cluster cells, find marker genes, filter low-quality cells, gene expression matrix, doublet removal, normalize counts, dimensionality reduction, cell clustering, QC single-cell, filtered_feature_bc_matrix, cellranger output, 10X h5, scrublet, cell ranger, count matrix, find cell types, batch effect, integration, neighborhood graph, or differential expression genes.Altele★ 72
- scgptaipoch/open-scienceEmbed and annotate single-cell expression data with scGPT, a foundation model for single-cell biology. Use this skill when: (1) Producing cell embeddings from an AnnData for clustering/integration, (2) Zero-shot or fine-tuned cell-type annotation, (3) Gene-level representation for perturbation/GRN tasks. For probabilistic single-cell models (scVI etc.), use the scvi-tools library.Știință★ 5.5K
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