reactome-database

Query the Reactome API for pathway enrichment analysis, identifier mapping, and diagram export.

Updated Jan 8, 2026
One-click install
npx skills add https://github.com/arslan9024/White-Caves --skill reactome-database-arslan9024
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: reactome-database
Source: https://github.com/arslan9024/White-Caves/tree/main/.agents/skills/reactome_database
Command: npx skills add https://github.com/arslan9024/White-Caves --skill reactome-database-arslan9024

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires polite-http, and includes scripts (resource) and references (resource) components.

What problem does it solve? Researchers analyzing gene or protein lists need to know which biological pathways are statistically enriched, but interacting with the Reactome Analysis and Content Service APIs directly requires handling dozens of endpoints, tokens, and output formats manually. ## Core Features & Use Cases - Pathway Enrichment Analysis: Submit gene or protein lists for overrepresentation analysis with FDR and p-value filtering, then retrieve results later via tokens. - Identifier Mapping & Cross-Referencing: Map identifiers (UniProt, Ensembl, gene symbols, ChEBI) to Reactome entities and across external databases. - Pathway Navigation & Visualization: Traverse pathway hierarchies, inspect reaction participants, and export diagrams as PNG or SVG with gene highlighting. - Use Case: Given a list of differentially expressed genes like TP53, BRCA1, and EGFR, run an enrichment analysis, filter to significant pathways at FDR 0.05, and export a highlighted diagram of Cell Cycle, Mitotic (R-HSA-69278). ## Quick Start Ask the assistant to run a Reactome pathway enrichment analysis on your gene list and show the top significant pathways.

Frequently Asked Questions about reactome-database

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

FAQPage Schema
How do I run a pathway enrichment analysis on a gene list?▼

Use the analyze subcommand with your identifiers via --data or --file, for example: uv run scripts/reactome_analysis.py analyze --data "TP53,BRCA1,EGFR" --fdr 0.05 --output /tmp/enrich.json. Results are written to the output file and include a token for later retrieval.

What identifier types does Reactome analysis support?▼

Reactome auto-detects many identifier types including gene symbols (TP53), UniProt (P04637), Ensembl (ENSG00000141510), ChEBI, OMIM, EntrezGene, miRBase, RefSeq, and Affymetrix. No pre-conversion is needed before submitting a list.

How do I retrieve Reactome results after the analysis finishes?▼

Every analysis returns a token that remains valid for 7 days. Use token-result, token-not-found, or download-result subcommands with that token to fetch the full result, unmapped identifiers, or CSV exports without resubmitting data.

Can I export Reactome pathway diagrams with highlighted genes?▼

Yes, the diagram subcommand exports pathway diagrams as PNG, SVG, JPG, or GIF. Pass --highlight with identifiers like TP53 to flag them in the image, and use reaction-diagram for individual reaction visualizations.

Why is my Reactome output file too large to read?▼

Commands like species-comparison can return very large JSON payloads. Use the --summary flag to truncate lists to 100 items, and process large output files with jq or a script instead of loading them fully into context.