bio-single-cell-markers-annotation
CommunityFind cluster markers and annotate cell types.
Data & Analytics#scanpy#differential-expression#seurat#scrna-seq#marker-genes#cell-type-annotation#gene-set-scoring
Authorya-way
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Find marker genes and annotate cell types in single-cell RNA-seq data analyzed with Seurat (R) or Scanpy (Python). This skill accelerates differential expression analysis between clusters, identifies cluster-specific markers, and supports scoring gene sets to infer cell identities.
Core Features & Use Cases
- Marker discovery across clusters using statistical tests (e.g., Wilcoxon, MAST) to identify robust marker genes.
- Manual or automated cell-type annotation based on curated marker sets and expression patterns.
- Gene-set scoring and visualization readiness (score_genes, DotPlot, Heatmap) to interpret cluster identities.
- Export of marker lists and integration with both Seurat and Scanpy workflows for downstream reporting.
Quick Start
Run marker discovery for each cluster and annotate cell types using your Seurat or Scanpy workflow.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: bio-single-cell-markers-annotation Download link: https://github.com/ya-way/cytoclaw-skills/archive/main.zip#bio-single-cell-markers-annotation Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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