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scrna-celltype-annotation

Annotate scRNA-seq clusters using DGE markers and literature citations.

Updated Aug 27, 2026
Search Tags:#bioinformatics#single-cell#annotation#scRNA-seq#gene expression#literature retrieval
One-click install
npx skills add https://github.com/hhx465453939/Claude_skill_pool --skill scrna-celltype-annotation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scrna-celltype-annotation
Source: https://github.com/hhx465453939/Claude_skill_pool/tree/main/skills.gemini/scrna-celltype-annotation
Command: npx skills add https://github.com/hhx465453939/Claude_skill_pool --skill scrna-celltype-annotation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates the process of annotating single-cell RNA sequencing (scRNA-seq) clusters with precise cell types and provides robust literature-based evidence, streamlining the analysis and reporting workflow.

Core Features & Use Cases

  • Automated Cell Type Annotation: Assigns both major and minor cell type labels to clusters based on differential gene expression (DGE) markers.
  • Literature-Based Evidence: Retrieves and cites relevant scientific literature (e.g., from PubMed, OpenAlex) to support each annotation.
  • R Recode Code Generation: Produces R code for easy integration of annotations back into Seurat objects.
  • Structured Markdown Reports: Generates comprehensive reports detailing annotations, supporting evidence, and R code.
  • Use Case: After running differential expression analysis on your scRNA-seq data, use this Skill to automatically identify the cell types within each cluster and generate a report with citations for your publication.

Quick Start

Use the scrna-celltype-annotation skill to annotate cell clusters from the provided Seurat DGE results CSV file and generate a markdown report with R recode code.

Frequently Asked Questions about scrna-celltype-annotation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I annotate scRNA-seq clusters using differential gene expression markers?▼

You can annotate scRNA-seq clusters by providing a CSV file of differential gene expression markers to assign major and minor cell types, generating a structured Markdown report with R recode code and literature citations.

Can I automatically retrieve literature evidence for single-cell annotation?▼

Yes, automated single-cell annotation retrieves scientific literature from PubMed and OpenAlex to support each cell type assignment with citations and evidence descriptions in a structured report.

How do I generate R code to recode Seurat cluster identities after cell type annotation?▼

The annotation process generates R recode functions within a Markdown report, allowing you to easily integrate major and minor cell type labels back into your Seurat objects.

Does single-cell cluster annotation work with Seurat differential expression results?▼

Yes, the annotation accepts Seurat differential gene expression results formatted as a CSV file, using the DGE markers to identify cell types within each cluster.

What is the best way to assign both major and minor cell types to single-cell clusters?▼

The best way is to automate cluster annotation using DGE markers combined with literature retrieval, which assigns both major and minor cell type labels and generates a publication-ready report.

What should a single-cell annotation report include for publication readiness?▼

A publication-ready single-cell annotation report should include major and minor cell type assignments, supporting scientific citations with evidence descriptions, and R recode code for Seurat integration.

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