--- name: reactome-database-76d1c01ef62b description: > 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. --- # 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 LICENSE_NOTIFICATION.txt does not already exist in this skill 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 ` 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`: ```bash uv run scripts/reactome_analysis.py [options] --output /tmp/out.json ``` **To list all available subcommands and flags**, run: ```bash 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 ```bash 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 ```bash 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: ```bash 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 ```bash 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 ```bash 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 ```bash 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): ```bash 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: ```bash 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: ```bash 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: ```bash 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: ```bash 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 ```bash uv run scripts/reactome_analysis.py search --query "TP53 apoptosis" --output /tmp/results.json ``` ### 13. Query Entry by ID ```bash uv run scripts/reactome_analysis.py query --id R-HSA-69278 --output /tmp/entry.json ``` ### 14. Report & Species Comparison ```bash 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 --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](references/api_reference.md). --- Source attribution: mkurman Original project: https://github.com/mkurman/zorai/blob/d06ee7597049567dab92db22d41b2764cf89094a/skills/scientific-skills-gdm/reactome_database/SKILL.md License: Apache-2.0 License information: https://www.apache.org/licenses/LICENSE-2.0 Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. 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See the License for the specific language governing permissions and limitations under the License. # Mega AI Hub resource metadata Creator / publisher: mkurman Original project: https://github.com/mkurman/zorai/blob/d06ee7597049567dab92db22d41b2764cf89094a/skills/scientific-skills-gdm/reactome_database/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Education & Research, Healthcare & Life Sciences Roles: Business Intelligence Analyst, Clinical Research, Data Analyst, Market Research Analyst, Researcher Specialties: API Tools: Reactome Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 3c8cc5e29ff9bb86beacc9767a0c4b9b2dbc9243b20a4297ed1d277e85df7196