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spatial_enrichment

Perform ORA or GSEA pathway enrichment on spatial transcriptomics data.

155|26|Updated Mar 14, 2026
Search Tags:#pathway analysis#GSEA#spatial transcriptomics#enrichment analysis#gene sets#ORA
One-click install
npx skills add https://github.com/TianGzlab/OmicsClaw --skill spatial-enrichment
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: spatial_enrichment
Source: https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-enrichment
Command: npx skills add https://github.com/TianGzlab/OmicsClaw --skill spatial-enrichment

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires scanpy, gseapy, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the complex process of identifying biological pathways and gene sets within spatial transcriptomics data, which would otherwise require manual gene list extraction and external tool usage.

Core Features & Use Cases

  • Automated Enrichment Analysis: Performs Over-representation Analysis (ORA) or Gene Set Enrichment Analysis (GSEA) on spatial transcriptomics data.
  • Built-in Gene Sets: Utilizes curated gene sets (Hallmark, GO, KEGG, Reactome) for immediate analysis.
  • Use Case: After identifying distinct cell clusters in your spatial data, use this Skill to automatically determine which biological pathways are significantly active within each cluster, aiding in the interpretation of tissue microenvironments.

Quick Start

Run pathway enrichment analysis on the provided spatial data file 'preprocessed.h5ad'.

Frequently Asked Questions about spatial_enrichment

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

FAQPage Schema
How do I perform pathway enrichment analysis on spatial transcriptomics data?▼

You can perform pathway enrichment on spatial transcriptomics data by running ORA or GSEA on differential expression results to identify over-represented biological pathways within specific cell clusters.

What biological pathways are active in specific spatial transcriptomics clusters?▼

To identify active biological pathways in spatial clusters, apply gene set enrichment analysis using curated gene sets like Hallmark, GO, KEGG, or Reactome to your spatial differential expression results.

Can I use scanpy for gene set enrichment analysis?▼

Yes, scanpy is used for spatial data handling and preprocessing, while gseapy is utilized optionally for advanced gene set enrichment analysis methods like GSEA and ORA.

What is the difference between ORA and GSEA for spatial transcriptomics?▼

Over-representation Analysis (ORA) identifies over-represented pathways from a subset of differentially expressed genes, while Gene Set Enrichment Analysis (GSEA) evaluates ranked gene lists to detect pathway activity.

Do I need preprocessed h5ad files for spatial enrichment analysis?▼

Yes, you need a preprocessed h5ad file containing spatial transcriptomics data with identified cell clusters, which serves as the input for automated pathway and gene set enrichment analysis.

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