mims-harvard/tooluniverse-metabolomics-pathway
skills/tooluniverse-metabolomics-pathway/SKILL.md
Metabolomics pathway analysis — metabolite identification (HMDB, KEGG, ChEBI), pathway mapping (Reactome, KEGG, MetaCyc), disease associations, enzyme/gene linkage. Use for metabolite-to-pathway-to-disease connections, BridgeDb-based ID conversion, and integrating metabolomics with gene-level pathway analyses.
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SKILL.md
- name:
- tooluniverse-metabolomics-pathway
- description:
- Metabolomics pathway analysis — metabolite identification (HMDB, KEGG, ChEBI), pathway mapping (Reactome, KEGG, MetaCyc), disease associations, enzyme/gene linkage. Use for metabolite-to-pathway-to-disease connections, BridgeDb-based ID conversion, and integrating metabolomics with gene-level pathway analyses.
- disable-model-invocation:
- true
Metabolomics Pathway Analysis
Identify metabolites, map to metabolic pathways, find disease associations, and connect to enzymes/genes.
Domain Reasoning
Metabolite-to-pathway mapping requires correct, database-specific identifiers. HMDB IDs link to KEGG/Reactome but must be converted via BridgeDb; PubChem CIDs need explicit cross-referencing. Always verify metabolite identity first: the same common name can refer to structurally distinct isomers, and PubChem names frequently differ from CTD/KEGG names.
LOOK UP DON'T GUESS
- Pathway membership: call
MetaCyc_get_compound,KEGG_get_compound, orReactomeContent_search - Cross-database IDs: use
BridgeDb_xrefs - Enzyme-metabolite relationships: use
CTD_get_chemical_gene_interactionsorKEGG_get_compound - Disease associations: query
Metabolite_get_diseasesorCTD_get_chemical_diseases
COMPUTE, DON'T DESCRIBE
When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.
Workflow
Phase 0: Identify & Resolve → Phase 1: Characterize → Phase 2: Pathway Map →
Phase 3: Enzyme/Gene Linkage → Phase 4: Disease Associations → Phase 5: Cross-DB Enrichment → Report
Phase 0: Metabolite Identification & Resolution
By Name
Metabolite_search: query (REQUIRED), search_type ("name"/"formula"). Returns PubChem matches with CID, name, formula, MW, SMILES.
MetabolomicsWorkbench_search_compound_by_name: name (REQUIRED). Cross-reference with RefMet.
By Mass/Formula
MetabolomicsWorkbench_search_by_mz: mz (REQUIRED), adduct (e.g., "M+H"), tolerance. Uses moverz/REFMET/{mz}/{adduct}/{tolerance}.
MetabolomicsWorkbench_search_by_exact_mass: exact_mass (REQUIRED), tolerance. Uses moverz/REFMET/{mass}/M/{tolerance}.
By ID
Metabolite_get_info: compound_name, hmdb_id (e.g., "HMDB0000122"), or pubchem_cid. Returns HMDB ID, CID, InChIKey, classification.
KEGG_get_compound: compound_id (e.g., "C00031"). Returns linked pathways, enzymes, reactions.
ID Cross-Referencing
BridgeDb_xrefs: identifier (REQUIRED), source (REQUIRED: "Ch"=HMDB, "Cs"=ChemSpider, "Ck"=KEGG, "Ce"=ChEBI), target (optional).
BridgeDb_search: query (REQUIRED), organism. Free-text metabolite search.
Phase 1: Metabolite Characterization
Metabolite_get_info: classification (super_class/class/sub_class), biological_roles, cellular_locations.
MetabolomicsWorkbench_get_refmet_info: refmet_name (REQUIRED). Standardized RefMet classification.
KEGG_get_compound: linked enzyme/reaction/pathway IDs.
Phase 2: Pathway Mapping
MetaCyc
MetaCyc_search_pathways:query(keyword search, e.g., "glycolysis")MetaCyc_get_pathway:pathway_id(e.g., "GLYCOLYSIS") -- reactions, enzymes, compoundsMetaCyc_get_compound:compound_id(e.g., "PYRUVATE") -- pathways it participates inMetaCyc_get_reaction:reaction_id-- substrates, products, enzymes
KEGG
KEGG_get_gene_pathways:gene_id(e.g., "hsa:5230") -- pathways for enzyme geneKEGG_get_pathway_genes:pathway_id(e.g., "hsa00010") -- all genes in pathway
Reactome
ReactomeContent_search:query,types(e.g., "Pathway"),speciesReactome_get_pathway:id(e.g., "R-HSA-70171")ReactomeAnalysis_pathway_enrichment:identifiers(space-separated string, NOT array)Reactome_map_uniprot_to_pathways:uniprot_id
Phase 3: Enzyme & Gene Linkage
CTD_get_chemical_gene_interactions: input_terms (chemical name). Returns interacting genes.
KEGG_get_gene_pathways: which pathways an enzyme gene participates in.
BridgeDb_attributes: identifier, source, organism. Get attributes for identifier.
Workflow: KEGG compound -> enzyme IDs -> MetaCyc reaction -> enzyme names -> Reactome uniprot -> pathways -> MyGene for gene info.
Phase 4: Disease Associations
CTD_get_chemical_diseases: input_terms (chemical name, MeSH, CAS RN). Curated associations with direct/inferred evidence.
CTD_get_gene_diseases: input_terms (gene name). For metabolite-processing genes from Phase 3.
Metabolite_get_diseases: compound_name/hmdb_id/pubchem_cid, limit (default 50). CTD-backed.
Phase 5: Cross-Database Enrichment
MetabolomicsWorkbench_get_study: study_id (e.g., "ST000001").
MetabolomicsWorkbench_get_compound_by_pubchem_cid: pubchem_cid.
PubMed_search_articles / EuropePMC_search_articles: literature context.
For metabolite list enrichment: (1) convert names to gene/enzyme IDs via CTD, (2) run ReactomeAnalysis_pathway_enrichment with space-separated identifiers, (3) use KEGG_get_gene_pathways per enzyme.
Common Mistakes to Avoid
| Mistake | Correction | |---------|-----------| | Array to ReactomeAnalysis_pathway_enrichment | Must be space-separated string | | HMDB IDs in CTD_get_chemical_diseases | CTD uses common names or MeSH IDs | | Not resolving names first | Always start with Metabolite_search | | gene_id without organism prefix for KEGG | Need "hsa:5230" not "5230" | | Expecting HMDB API | No open API; use Metabolite_get_info (PubChem-backed) | | PubChem title to CTD when names differ | Try both PubChem name and common synonyms | | MetabolomicsWorkbench exactmass | Use moverz/REFMET/{mass}/M/{tolerance} (exactmass broken) |
Fallback Strategies
- Metabolite_search empty -> MetabolomicsWorkbench_search_compound_by_name or KEGG_get_compound
- MetaCyc not found -> KEGG or Reactome pathways
- CTD empty for disease -> Metabolite_get_diseases with HMDB/CID
- No KEGG compound ID -> BridgeDb_xrefs from HMDB/ChEBI
- exactmass fails -> search_by_mz with M+H adduct
- Need enzyme genes -> CTD_get_chemical_gene_interactions
Evidence Grading
| Tier | Criteria | Sources | |------|----------|---------| | T1 | Curated disease association, direct evidence | CTD curated, OMIM | | T2 | Multiple database pathway concordance | MetaCyc + KEGG + Reactome agreement | | T3 | Inferred or single-database | CTD inferred, single pathway DB | | T4 | Computational prediction or text-mining | Literature, RefMet classification |
Limitations
- HMDB has no open API; use Metabolite_get_info (PubChem-backed).
- MetaCyc pathways are reference (not organism-specific like KEGG).
- CTD can return very large sets for common metabolites (22K+ for acetaminophen).
- ReactomeAnalysis expects gene/protein IDs, not metabolite IDs directly.
- BridgeDb coverage depends on the metabolite being in mapping databases.
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