Spatial Omics Skills Index
De la autor
Skills for spatial transcriptomics analysis including single-cell to spatial mapping (MOSCOT), 3D visualization (PyVista), and related spatial workflows.
Instalare
npx skills add BioTender-max/awesome-bio-agent-skills --skill 'Spatial Omics Skills Index' -a claude-code
Se instalează în .claude/skills/Spatial-Omics-Skills-Index/ · 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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Verificări de siguranță pe SKILL.md
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De ce 74
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- Omics Analysis Skills IndexBioTender-max/awesome-bio-agent-skillsSkills for single-cell and spatial omics data analysis. Best practices, code snippets, and workflows for the scverse ecosystem.Date★ 215
- OpenST Skills IndexBioTender-max/awesome-bio-agent-skillsSkills for Open-ST spatial transcriptomics data processing, from raw BCL files to spatially-resolved single-cell h5ad objects.Altele★ 215
- scvi-toolsK-Dense-AI/scientific-agent-skillsFits probabilistic models for single-cell omics, including scVI batch integration, scANVI annotation, totalVI CITE-seq, MultiVI RNA/ATAC integration, and posterior differential expression. Use for generative modeling, reference mapping, multimodal analysis, or model-based uncertainty; use scanpy for standard preprocessing and exploratory analysis.Altele★ 56.2K
- mapkitrshankras/claude-code-apple-skillsMapKit and GeoToolbox skills — PlaceDescriptor patterns, geocoding, and cross-service place identifiers with MapKit integration. Use when working with maps, place data, or geocoding.Altele★ 863
- spatial-domain-detectionjaechang-hits/SciAgent-SkillsSpatial domain detection (tissue regions / niches) for spatial transcriptomics: SpaGCN (expression + spatial graph + H&E histology, Visium/ST), GraphST (self-supervised graph contrastive embedding, spots or cells) and UTAG (spatial message passing for Xenium/MERFISH/CosMx/IMC cells). Outputs a domain label per spot or cell, boundary refinement, cross-method agreement (ARI) and domain marker genes. For niches defined by the cell type composition of annotated cells use Step 7 of spatial-transcriptomics-cell-type-annotation; for neighbourhood enrichment and spatial statistics use spatial-transcriptomics-analysis-squidpy.Altele★ 385
- spatial-transcriptomics-cell-type-annotationjaechang-hits/SciAgent-SkillsSpatial transcriptomics cell type annotation for single-cell-resolution platforms (Xenium, MERFISH, CosMx, SeqFISH): CELLxGENE reference download, Harmony label transfer, per-cluster marker evidence naming lineages then subtypes, spatial niches. Visium/Slide-seq spots: GPU -> spatial-transcriptomics-deconvolution-cell2location; CPU -> spatial-mapping-tangram (cell types: per-spot proportions); no reference -> spatial-domain-detection (regions: domains from markers). Beyond labels (microenvironment, arrangement, spatial patterns): read spatial-transcriptomics-analysis-squidpy before asking the user.Documente★ 385
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