reactome-database
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.
How do I install this agent skill?
npx skills add https://github.com/google-deepmind/science-skills --skill reactome-databaseIs this agent skill safe to install?
- Gen Agent Trust Hubpass
This skill provides a secure interface for querying the Reactome pathway database. It uses a Python CLI to interact with official scientific APIs and follows established safety practices for data handling.
- Socketpass
No alerts
- Snykpass
Risk: LOW · No issues
What does this agent skill do?
Reactome Analysis & Content Service
Prerequisites
uv: Read theuvskill and follow its Setup instructions to ensureuvis installed and on PATH.- 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 useR-HSA-69278.
Core Rules
- Always use
--output: Every subcommand requires--output <file>to write results to a file. Never rely on stdout for large results. - Default species is Homo sapiens: Use
--speciesto override. - Tokens expire after 7 days: Store tokens from analysis results to retrieve them later without re-submitting data.
- Use
--fdrand--pvalueto filter: Enrichment results can be overwhelming. Filter with--fdr 0.05or--pvalue 0.01to focus on statistically significant pathways. - Identifier formats: Reactome auto-detects identifiers including gene symbols (TP53), UniProt (P04637), Ensembl (ENSG00000141510), ChEBI, OMIM, EntrezGene, and many more.
- Handle large outputs: For commands that return large data (like
species-comparison), use the--summaryflag to truncate lists and avoid exceeding workspace file size limits (1MB). - 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:
-
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 -
Inspect top pathways — examine
pathwaysFound, top pathway names, p-values, and FDR values in the output. -
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 -
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 -
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 -
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.
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/google-deepmind/science-skills/reactome-database">View reactome-database on skillZs</a>