reactome-database

Name: reactome-database
Availability: InStock
Author: robinbarvaag

Query the Reactome REST API for pathway analysis and enrichment.

Updated Jan 10, 2026

Search Tags:#bioinformatics #pathway analysis #systems biology #reactome #gene enrichment #molecular interactions

Ready to run

npx skills add https://github.com/robinbarvaag/poynt --skill reactome-database-robinbarvaag

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: reactome-database
Source: https://github.com/robinbarvaag/poynt/tree/main/.github/skills/reactome-database
Command: npx skills add https://github.com/robinbarvaag/poynt --skill reactome-database-robinbarvaag

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, reactome2py, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides access to Reactome's comprehensive database of biological pathways and molecular interactions, enabling in-depth systems biology research.

Core Features & Use Cases

Pathway Analysis: Perform overrepresentation and expression analysis on gene lists.
Data Retrieval: Query specific pathway information, reactions, and molecular entities.
Use Case: Analyze a list of differentially expressed genes to identify significantly enriched biological pathways and visualize their relationships.

Quick Start

Use the reactome-database skill to perform overrepresentation analysis on the gene list provided in 'my_genes.txt'.

Frequently Asked Questions about reactome-database

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 is performed by submitting a list of differentially expressed genes to the Reactome Analysis service for overrepresentation analysis. This identifies significantly enriched biological pathways and maps genes to specific molecular interactions within those pathways.

What is the best way to query biological pathways and molecular interactions programmatically?▼

Querying biological pathways and molecular interactions is best handled through the Reactome REST API using the reactome2py Python package. This provides programmatic access to the Content service for data retrieval and the Analysis service for computational systems biology studies.

Can I retrieve specific disease pathways and molecular entities using Python?▼

Yes, you can retrieve specific disease pathways and molecular entities using Python. The skill queries the Reactome REST API Content service to extract data on specific reactions, pathway information, and molecular entities relevant to disease research.

Does this pathway analysis approach support expression analysis for systems biology studies?▼

Yes, this pathway analysis approach supports expression analysis for systems biology studies. The Reactome Analysis service handles both overrepresentation and expression analysis on gene lists, enabling comprehensive computational analysis of biological pathway relationships.

Do I need the reactome2py package to access Reactome database content?▼

Yes, you need the reactome2py package along with the requests library to access Reactome database content. These dependencies provide the programmatic interface required to query the REST API and retrieve pathway analysis data.

What are the limitations of using the Reactome REST API for pathway analysis?▼

The limitations of using the Reactome REST API for pathway analysis include dependency on external service availability and the scope of the Reactome database itself. Data retrieval and computational analysis are constrained by the current Content and Analysis service endpoints.