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gene-set-enrichment

Identify enriched pathways, GO terms, and disease associations from gene lists.

18|2|Updated Oct 20, 2025
Search Tags:#research#AI#bioinformatics#genomics#gene analysis#pathways#disease
One-click install
npx skills add https://github.com/monarch-initiative/deep-research-client --skill gene-set-enrichment
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: gene-set-enrichment
Source: https://github.com/monarch-initiative/deep-research-client/tree/main/.claude/skills/gene-set-enrichment
Command: npx skills add https://github.com/monarch-initiative/deep-research-client --skill gene-set-enrichment

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires deep-research-client.

What problem does it solves? Interpreting lists of genes from genomic experiments (e.g., differential expression) is a complex, manual, and often overwhelming task. This Skill automates the process of identifying common biological pathways, functions, and disease associations, transforming raw gene lists into actionable biological insights.

Core Features & Use Cases

  • Pathway & Disease Analysis: Automatically identify enriched biological pathways (KEGG, Reactome), processes (GO terms), and disease connections (OMIM) for your gene sets.
  • Functional Interpretation: Discover common biological functions, tissue-specific expression patterns, and potential drug targets associated with your genes.
  • Template-Based Analysis: Utilize a reusable template to easily input gene lists and specify analysis context, ensuring consistent and reproducible results.
  • Use Case: After identifying 50 upregulated genes in a cancer study, use this Skill to quickly understand what biological processes these genes are involved in, which diseases they are linked to, and potential therapeutic implications, saving hours of manual database searching.

Quick Start

Perform quick gene set enrichment analysis on a list of human genes

uv run deep-research-client research
--template .claude/skills/gene-set-enrichment/examples/enrichment_template.md
--var "geneset=APOH APP COL3A1 VEGFA THBD"
--var "organism=human"
--provider perplexity
--model sonar-deep-research

Frequently Asked Questions about gene-set-enrichment

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

FAQPage Schema
How do I interpret a list of genes from differential expression results?▼

Gene set enrichment analysis identifies common biological pathways, functions, and disease associations in your gene lists, transforming raw data into actionable insights. This Skill automates the process by analyzing KEGG pathways, GO terms, and disease connections like OMIM to reveal what biological processes your genes are involved in.

Can I analyze gene sets for pathway and disease associations automatically?▼

Yes. This Skill automatically identifies enriched biological pathways, GO term processes, tissue-specific expression patterns, and disease links for your genes. It supports template-based input and multi-provider analysis via Perplexity, OpenAI, and FutureHouse to generate publication-ready summaries.

What's the fastest way to find biological insights from genomic experiment results?▼

Use template-based gene set enrichment analysis to automate pathway discovery and disease mapping. Rather than manual database searching, this Skill processes gene lists to identify functions, drug targets, tissue contexts, and interactions in minutes, saving hours of interpretation work.

Do I need prior bioinformatics experience to analyze gene enrichment?▼

No. The Skill uses reusable templates and requires only your gene list and organism type as input. It handles database lookups, enrichment calculations, and multi-provider analysis internally, making it accessible for researchers without deep bioinformatics expertise.

What output formats does gene set enrichment analysis produce?▼

The Skill outputs pathways, GO terms, disease links, tissue expression data, protein interactions, and publication-ready summaries. Results integrate citations and functional interpretations, ready for reports or follow-up drug-target discovery workflows.

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