AutoGineer
Generated banner for Reactome Database
Generated logo for Reactome Database

Reactome Database

Google DeepMindOfficialPublished by Google DeepMind

  • Skill
  • Tool integration
  • Science and research
  • Apache-2.0
  • Low risk
  • Has scripts
Download ZIP

From the author

Query the Reactome database (Analysis and Content Services). Use when the user asks about pathway analysis, gene list enrichment, retrieving results by token, finding unmapped or not-found identifiers, mapping identifiers, reaction participants (inputs, outputs), pathway hierarchy (including top-level pathways), diagram export, cross-reference mapping, or searching the knowledgebase.
— the description by Google DeepMind

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The Reactome database skill provides a command-line interface to the Reactome Analysis and Content Services. It enables researchers to perform pathway enrichment analysis on gene or protein lists, map identifiers across species, navigate pathway hierarchies, and retrieve detailed information about reactions and participants. The tool supports advanced features like diagram generation, cross-reference mapping, and token-based result management for large datasets.

What it does

  • Performs overrepresentation and expression analysis on gene or protein lists.
  • Maps biological identifiers across different species and databases.
  • Navigates pathway hierarchies and retrieves reaction-level details.
  • Exports pathway and reaction diagrams in PNG or SVG formats.
  • Manages analysis results using persistent tokens for later retrieval.
  • Searches the Reactome knowledgebase for specific biological entities.

When to use it

  • When you need to identify statistically significant biological pathways for a list of genes.
  • When you need to visualize gene involvement in specific cellular processes.
  • When you need to map gene symbols or protein IDs to Reactome stable identifiers.
  • When you are exploring the hierarchical structure of biological pathways.
  • When you need to retrieve detailed participant lists for a specific reaction.

Advantages

  • Provides direct access to curated, open-source biological pathway data.
  • Supports automated analysis workflows for large-scale gene lists.
  • Allows for visual pathway exploration through diagram exports.
  • Facilitates cross-species comparisons and identifier mapping.
  • Enables efficient data handling through token-based result retrieval.

Usage examples

“Perform a pathway enrichment analysis on the following gene list: TP53, BRCA1, EGFR.”
The agent runs the analysis service and saves the enrichment results, including p-values and FDR, to a JSON file.
“Export a diagram for the Mitotic Cell Cycle pathway and highlight TP53.”
The agent generates a PNG diagram of the specified pathway with the TP53 protein highlighted.
“Find all reaction participants for the reaction R-HSA-6804194.”
The agent retrieves and saves the list of inputs, outputs, and catalysts for the specified reaction.
“Map the gene symbol TP53 to its Reactome cross-references.”
The agent queries the database and returns a JSON file containing the cross-reference mapping for the identifier.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/google-deepmind/reactome-database/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip reactome-database.zip -d .agents/skills

Documentation by Google DeepMind

Reactome Analysis & Content Service

Prerequisites

  1. uv: Read the uv skill and follow its Setup instructions to ensure uv is installed and on PATH.

  2. User Notification: If .licenses/reactome_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://reactome.org/license and https://reactome.org/cite, then (2) create the file recording the notification text and timestamp.

Overview

Reactome is a free, open-source, curated pathway database. This skill wraps both the Analysis Service (https://reactome.org/AnalysisService/) and the Content Service (https://reactome.org/ContentService/) providing pathway enrichment analysis, identifier mapping, reaction details, pathway hierarchy navigation, diagram export, cross-reference mapping, and search.

When to Use This Skill

  • Performing pathway enrichment (overrepresentation) analysis on gene/protein lists

  • Retrieving analysis results using a token from previous enrichment

  • Identifying which genes or proteins were not found in a pathway analysis

  • Analyzing gene expression data against pathway annotations

  • Mapping identifiers to Reactome entities across species

  • Retrieving reaction participants (inputs, outputs, catalysts, regulators)

  • Navigating pathway hierarchy and listing top-level pathways

  • Finding which complexes or sets contain a protein

  • Exporting pathway/reaction diagrams (PNG/SVG) with gene highlighting

  • Cross-referencing identifiers across databases (UniProt, Ensembl, etc.)

  • Searching the Reactome knowledgebase

  • Downloading analysis reports (PDF, CSV, JSON)

  • Comparing pathways across species

Common Species IDs

Reference list for common research organisms:

  • Homo sapiens

    • ID: 9606

  • Mus musculus (Mouse)

    • ID: 48892

  • Rattus norvegicus (Rat)

    • ID: 48895

Common Pathway IDs

Reference list for commonly used Reactome pathway stable IDs:

  • Cell Cycle

    • Stable ID: R-HSA-1640170

    • Notes: Top-level pathway (broad)

  • Cell Cycle, Mitotic

    • Stable ID: R-HSA-69278

    • Notes: Specific sub-pathway — use this for diagrams and drill-downs

  • Immune System

    • Stable ID: R-HSA-168256

    • Notes: Top-level pathway

  • Signal Transduction

    • Stable ID: R-HSA-162582

    • Notes: Top-level pathway

  • Gene Expression

    • Stable ID: R-HSA-74160

    • Notes: Top-level pathway

  • Programmed Cell Death

    • Stable ID: R-HSA-5357801

    • Notes: Top-level pathway

Important: When the user asks for a "Cell Cycle" diagram or analysis, prefer the specific Cell Cycle, Mitotic pathway (R-HSA-69278) unless the user explicitly requests the top-level overview. The examples throughout this document use R-HSA-69278.

Core Rules

  1. Always use --output: Every subcommand requires --output <file> to write results to a file. Never rely on stdout for large results.

  2. Default species is Homo sapiens: Use --species to override.

  3. Tokens expire after 7 days: Store tokens from analysis results to retrieve them later without re-submitting data.

  4. Use --fdr and --pvalue to filter: Enrichment results can be overwhelming. Filter with --fdr 0.05 or --pvalue 0.01 to focus on statistically significant pathways.

  5. Identifier formats: Reactome auto-detects identifiers including gene symbols (TP53), UniProt (P04637), Ensembl (ENSG00000141510), ChEBI, OMIM, EntrezGene, and many more.

  6. Handle large outputs: For commands that return large data (like species-comparison), use the --summary flag to truncate lists and avoid exceeding workspace file size limits (1MB).

  7. Notification: If this skill is used, ensure this is mentioned in the output.

Tool Execution

The CLI tool is at scripts/reactome_analysis.py. Run with uv:

uv run scripts/reactome_analysis.py <command> [options] --output /tmp/out.json

To list all available subcommands and flags, run:

uv run scripts/reactome_analysis.py --help

Use --help to verify available subcommands or flags before executing an unfamiliar command.

Feature Domains

1. Database Info
uv run scripts/reactome_analysis.py db-version --output /tmp/version.json
uv run scripts/reactome_analysis.py db-name --output /tmp/name.json
2. Single Identifier Analysis
uv run scripts/reactome_analysis.py identifier --id TP53 --output /tmp/tp53.json
uv run scripts/reactome_analysis.py identifier-projection --id TP53 --output /tmp/tp53_proj.json
3. Batch Analysis (Enrichment)

Submit a list of identifiers for overrepresentation or expression analysis:

uv run scripts/reactome_analysis.py analyze --data "TP53,BRCA1,EGFR" --output /tmp/enrich.json
uv run scripts/reactome_analysis.py analyze --file genes.txt --output /tmp/enrich.json
uv run scripts/reactome_analysis.py analyze-projection --data "TP53,BRCA1" --output /tmp/proj.json
uv run scripts/reactome_analysis.py analyze --data "TP53,BRCA1" --fdr 0.05 --output /tmp/sig.json

Common options: --page-size (alias --limit), --page (alias --offset), --sort-by, --order, --resource, --species, --fdr, --pvalue.

4. Token-Based Result Retrieval
uv run scripts/reactome_analysis.py token-result --token TOKEN --output /tmp/result.json
uv run scripts/reactome_analysis.py token-not-found --token TOKEN --output /tmp/notfound.json
uv run scripts/reactome_analysis.py token-resources --token TOKEN --output /tmp/resources.json
uv run scripts/reactome_analysis.py token-found-entities --token TOKEN --pathway R-HSA-69278 --output /tmp/found.json
uv run scripts/reactome_analysis.py token-filter-species --token TOKEN --species-filter 9606 --output /tmp/filtered.json
uv run scripts/reactome_analysis.py token-reactions-pathway --token TOKEN --pathway R-HSA-69278 --output /tmp/rxns.json
5. Download Results
uv run scripts/reactome_analysis.py download-result --token TOKEN --output /tmp/full.json
uv run scripts/reactome_analysis.py download-pathways --token TOKEN --output /tmp/pathways.csv
uv run scripts/reactome_analysis.py download-found --token TOKEN --output /tmp/found.csv
uv run scripts/reactome_analysis.py download-not-found --token TOKEN --output /tmp/notfound.csv
6. Identifier Mapping
uv run scripts/reactome_analysis.py mapping --data "TP53,BRCA1" --output /tmp/mapped.json
uv run scripts/reactome_analysis.py mapping-projection --data "TP53" --output /tmp/mapped_proj.json
7. Reaction Participants & Mechanism of Action

Retrieve the molecular participants of a reaction (inputs, outputs, catalysts):

uv run scripts/reactome_analysis.py participants --id R-HSA-6804194 --output /tmp/participants.json
uv run scripts/reactome_analysis.py participating-entities --id R-HSA-6804194 --output /tmp/entities.json
8. Complex & Set Membership

Find which complexes or sets contain a given entity:

uv run scripts/reactome_analysis.py component-of --id R-HSA-69488 --output /tmp/complexes.json
9. Pathway Hierarchy Navigation

Move up (ancestors) or down (contained events) the pathway hierarchy:

uv run scripts/reactome_analysis.py event-ancestors --id R-HSA-69278 --output /tmp/ancestors.json
uv run scripts/reactome_analysis.py contained-events --id R-HSA-69278 --output /tmp/steps.json
uv run scripts/reactome_analysis.py top-pathways --output /tmp/top.json
uv run scripts/reactome_analysis.py low-pathways --id R-HSA-69488 --output /tmp/low.json
10. Diagram Export

Export pathway or reaction diagrams as PNG/SVG, with optional gene highlighting:

uv run scripts/reactome_analysis.py diagram --id R-HSA-69278 --output /tmp/diagram.png
uv run scripts/reactome_analysis.py diagram --id R-HSA-69278 --highlight TP53 --output /tmp/highlighted.png
uv run scripts/reactome_analysis.py diagram --id R-HSA-69278 --format svg --output /tmp/diagram.svg
uv run scripts/reactome_analysis.py reaction-diagram --id R-HSA-6804194 --output /tmp/rxn.png
11. Cross-Reference Mapping

Resolve identifiers to Reactome internal IDs and cross-references:

uv run scripts/reactome_analysis.py xref-mapping --id TP53 --output /tmp/xref.json
uv run scripts/reactome_analysis.py xref-mapping-batch --data "TP53,BRCA1" --output /tmp/xrefs.json
12. Search
uv run scripts/reactome_analysis.py search --query "TP53 apoptosis" --output /tmp/results.json
13. Query Entry by ID
uv run scripts/reactome_analysis.py query --id R-HSA-69278 --output /tmp/entry.json
14. Report & Species Comparison
uv run scripts/reactome_analysis.py report --token TOKEN --output /tmp/report.pdf
uv run scripts/reactome_analysis.py species-comparison --species-id 48892 --output /tmp/species.json
# Use --summary to truncate large output and avoid workspace file size limits
uv run scripts/reactome_analysis.py species-comparison --species-id 48892 --summary --output /tmp/species.json

Recipe: Interpreting Gene Set Enrichment

A step-by-step workflow for interpreting gene set enrichment results:

  1. Submit gene list with projection to human pathways: bash uv run scripts/reactome_analysis.py analyze-projection \ --data "TP53,BRCA1,EGFR,MYC,PTEN" --fdr 0.05 --output /tmp/enrichment.json

  2. Inspect top pathways — examine pathwaysFound, top pathway names, p-values, and FDR values in the output.

  3. Drill into a pathway — get its sub-events and reaction details: bash uv run scripts/reactome_analysis.py contained-events --id R-HSA-69278 --output /tmp/steps.json uv run scripts/reactome_analysis.py participants --id <reaction_id> --output /tmp/parts.json

  4. Visualise — export a diagram with your genes highlighted: bash uv run scripts/reactome_analysis.py diagram --id R-HSA-69278 \ --highlight "TP53,BRCA1" --output /tmp/diagram.png

  5. Check hierarchy — navigate up to see broader biological context: bash uv run scripts/reactome_analysis.py event-ancestors --id R-HSA-69278 --output /tmp/ancestors.json

  6. Cross-reference — map identifiers to other databases: bash uv run scripts/reactome_analysis.py xref-mapping --id TP53 --output /tmp/xrefs.json

Reference

For detailed API endpoint documentation, see references/api_reference.md.

Files

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Python

Security

What our scanner noticed· Low risk

  • Scripts that your agent may run

This skill includes scripts that your agent may run. Read them before you use it.

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by
Google DeepMind
Publisher
Google DeepMind (Official)
Source
google-deepmind/science-skills · skills/reactome_database · commit 4de6786
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Google DeepMind or Google DeepMind.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download reactome-database.zip