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seurat-single-cell-analysis

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Seurat v5 single-cell RNA-seq analysis in R.

Data & Analytics#visualization#r#single-cell#h5ad#seurat#rna-seq#go enrichment
AuthorKetomihine
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill enables researchers to perform comprehensive Seurat v5–based single-cell RNA-seq analysis in R, covering data loading, quality control, normalization, variable feature selection, dimensionality reduction, clustering, marker identification, and GO enrichment interpretation, all within a unified workflow.

Core Features & Use Cases

  • End-to-end workflow: Load .rds/.rdata objects, normalize data, identify highly variable features, run PCA/UMAP, construct neighbor graphs, cluster cells, and extract marker genes.
  • GO enrichment visualizations: Generate publication-ready GO plots for Biological Process, Cellular Component, and Molecular Function, with separate or combined formats.
  • Cross-platform workflows: Convert Seurat objects to H5AD to enable cross-platform analyses with Scanpy while preserving metadata and reductions.
  • Example: Analyze a PBMC dataset to discover cluster-specific markers and interpret enriched GO terms.

Quick Start

Load your .rds/.rdata Seurat object and run a basic Seurat workflow, then generate GO enrichment visualizations.

Dependency Matrix

Required Modules

None required

Components

Standard package

đŸ’» 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: seurat-single-cell-analysis
Download link: https://github.com/Ketomihine/my_skills/archive/main.zip#seurat-single-cell-analysis

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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