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tooluniverse-gene-enrichment

Perform gene enrichment and pathway analysis with gseapy, PANTHER, STRING, and Reactome.

2|Updated May 7, 2026
Search Tags:#bioinformatics#pathway analysis#reactome#string#panther#gene enrichment#gseapy
One-click install
npx skills add https://github.com/Teng-bio/codex-skills-hub --skill tooluniverse-gene-enrichment
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tooluniverse-gene-enrichment
Source: https://github.com/Teng-bio/codex-skills-hub/tree/main/skills/global/tooluniverse-gene-enrichment
Command: npx skills add https://github.com/Teng-bio/codex-skills-hub --skill tooluniverse-gene-enrichment

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires gseapy, pantherdb, stringdb, reactome, mygene, string, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps researchers conduct gene enrichment and pathway analysis by integrating various bioinformatics tools like gseapy, PANTHER, STRING, and Reactome, offering cross-validated results and comprehensive analysis.

Core Features & Use Cases

  • Comprehensive Enrichment: Offers a wide range of databases for gene ontology, KEGG, Reactome, WikiPathways, and MSigDB hallmarks.
  • Multiple ID Types: Handles gene symbols, Ensembl IDs, Entrez IDs, and UniProt IDs.
  • Custom Backgrounds: Allows users to define custom backgrounds for gene lists.
  • Multiple Testing Correction: Provides options for Benjamini-Hochberg, Bonferroni, and FDR correction methods.
  • Use Case: A researcher with a list of genes from a differential expression study can use this Skill to perform gene enrichment analysis and identify significant biological processes, molecular functions, or cellular components.

Quick Start

Run the gene enrichment analysis for your gene list using the tooluniverse-gene-enrichment skill. For example: tooluniverse-gene-enrichment analyze my_gene_list.txt --organism human --analysis_type ORA --enrichment_databases GO_BP,GO_MF,GO_CC,KEGG,Reactome

Frequently Asked Questions about tooluniverse-gene-enrichment

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

FAQPage Schema
How do I perform gene enrichment analysis on a list of differentially expressed genes?▼

Gene enrichment analysis identifies significantly over-represented biological pathways in a gene list. This Skill uses gseapy, PANTHER, STRING, and Reactome to cross-validate results across multiple databases for gene ontology, KEGG, and MSigDB hallmarks.

Can I use Ensembl IDs or UniProt IDs for pathway analysis instead of gene symbols?▼

Yes, pathway analysis supports multiple ID types including gene symbols, Ensembl IDs, Entrez IDs, and UniProt IDs. The Skill handles ID conversion and mapping automatically during the gene enrichment process across all integrated databases.

What is the best way to correct for multiple testing in gene enrichment analysis?▼

Multiple testing correction in gene enrichment analysis controls false positives. This Skill provides options for Benjamini-Hochberg, Bonferroni, and FDR correction methods to assess the statistical significance of enriched pathways and gene sets.

Does gseapy support custom background gene sets for enrichment analysis?▼

Yes, custom backgrounds are fully supported for enrichment analysis. You can define a specific background gene set to accurately calculate statistical significance relative to your experiment's unique biological context and organism.

How do I run Reactome and KEGG pathway analysis for human genes?▼

Reactome and KEGG pathway analysis for human genes is executed by specifying the organism parameter. The Skill integrates these databases alongside PANTHER and STRING to cross-validate identified enriched biological processes and molecular functions.

What are the limitations of using PANTHER and STRING for cross-validated pathway analysis?▼

Cross-validated pathway analysis using PANTHER and STRING relies on the database coverage and annotation quality of the selected organism. Limitations arise when specific gene sets lack sufficient pathway annotations or custom background sets are not properly formatted.

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