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tooluniverse-metabolomics-pathway

This Claude Code skill identifies metabolites from multiple databases (HMDB, KEGG, ChEBI, PubChem), maps them to metabolic pathways (Reactome, KEGG, MetaCyc), retrieves associated diseases, and links metabolites to enzymes and genes. Use it when analyzing metabolomics datasets to understand how identified metabolites participate in biochemical pathways, connect to disease states, and integrate with genomic or proteomic data through standardized cross-database identifier conversion via BridgeDb.

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git clone --depth 1 https://github.com/mims-harvard/ToolUniverse /tmp/tooluniverse-metabolomics-pathway && cp -r /tmp/tooluniverse-metabolomics-pathway/plugin/skills/tooluniverse-metabolomics-pathway ~/.claude/skills/tooluniverse-metabolomics-pathway
Después abre una sesión nueva de Claude Code; el skill carga automáticamente.

SKILL.md

# 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`, or `ReactomeContent_search`
- Cross-database IDs: use `BridgeDb_xrefs`
- Enzyme-metabolite relationships: use `CTD_get_chemical_gene_interactions` or `KEGG_get_compound`
- Disease associations: query `Metabolite_get_diseases` or `CTD_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, compounds
- `MetaCyc_get_compound`: `compound_id` (e.g., "PYRUVATE") -- pathways it participates in
- `MetaCyc_get_reaction`: `reaction_id` -- substrates, products, enzymes

### KEGG
- `KEGG_get_gene_pathways`: `gene_id` (e.g., "hsa:5230") -- pathways for enzyme gene
- `KEGG_get_pathway_genes`: `pathway_id` (e.g., "hsa00010") -- all genes in pathway

### Reactome
- `ReactomeContent_search`: `query`, `types` (e.g., "Pathway"), `species`
- `Reactome_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_
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