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Diagnoses rare diseases by matching patient phenotypes (HPO terms) to candidate diseases from Orphanet/OMIM, prioritizes gene panels, interprets ACMG variants, and analyzes protein structures. Use for diagnostic odyssey assistance and genetic-counseling differentials.
How this skill is triggered — by the user, by Claude, or both
Slash command
/tooluniverse:tooluniverse-rare-disease-diagnosisThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Systematic diagnosis support for rare diseases using phenotype matching, gene panel prioritization, and variant interpretation across Orphanet, OMIM, HPO, ClinVar, and structure-based analysis.
Systematic diagnosis support for rare diseases using phenotype matching, gene panel prioritization, and variant interpretation across Orphanet, OMIM, HPO, ClinVar, and structure-based analysis.
KEY PRINCIPLES:
When uncertain about any scientific fact, SEARCH databases first rather than reasoning from memory.
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.
Apply these strategies to form a 3-5 candidate differential, then use tools to confirm/refute:
Common pitfalls: Felty's (RA+splenomegaly+neutropenia) mimics infection; SLE nephritis mimics PSGN (check ASO); occupational exposures trigger autoimmunity (silica→scleroderma/RA/SLE).
| Tool | WRONG | CORRECT |
|---|---|---|
OpenTargets_get_associated_drugs_by_target_ensemblID | ensemblID | ensemblId |
ClinVar_get_variant_details | variant_id | id |
MyGene_query_genes | gene | q |
gnomad_get_variant | variant | variant_id |
Phase 0: Clinical Reasoning → 3-5 candidate differential
Phase 1: Phenotype → HPO terms (HPO_search_terms), core vs variable, onset, family history
Phase 2: Disease Matching → Orphanet_search_diseases, OMIM_search, DisGeNET_search_gene
Phase 3: Gene Panel → ClinGen validation, GTEx expression, prioritization scoring
Phase 3.5: Expression Context → CELLxGENE, ChIPAtlas for tissue/cell-type confirmation
Phase 3.6: Pathway Analysis → KEGG, IntAct for convergent pathways
Phase 4: Variant Interpretation → ClinVar, gnomAD frequency, CADD/AlphaMissense/EVE/SpliceAI, ACMG criteria
Phase 5: Structure Analysis → AlphaFold2, InterPro domains (for VUS)
Phase 6: Literature → PubMed, BioRxiv/MedRxiv, OpenAlex
Phase 7: Report Synthesis → Prioritized differential with next steps
Phase 2 - Disease Matching: Orphanet_search_diseases(operation="search_diseases", query=keyword) then Orphanet_get_genes(operation="get_genes", orpha_code=code). Score overlap: Excellent >80%, Good 60-80%, Possible 40-60%.
Phase 3 - Gene Panel: ClinGen classification drives inclusion (Definitive/Strong/Moderate = include; Limited = flag; Disputed/Refuted = exclude). Scoring: Tier 1 (top disease gene +5), Tier 2 (multi-disease +3), Tier 3 (ClinGen Definitive +3), Tier 4 (tissue expression +2), Tier 5 (pLI >0.9 +1).
Phase 4 - Variants: gnomAD frequency classes: ultra-rare <0.00001, rare <0.0001, low-freq <0.01. ACMG: PVS1 (null), PS1 (same AA), PM2 (absent pop), PP3 (computational), BA1 (>5% AF). 2+ concordant predictors strengthen PP3.
| Tier | Criteria |
|---|---|
| T1 (High) | Phenotype match >80% + gene match |
| T2 (Medium-High) | Phenotype match 60-80% OR likely pathogenic variant |
| T3 (Medium) | Phenotype match 40-60% OR VUS in candidate gene |
| T4 (Low) | Phenotype <40% OR uncertain gene |
| Primary | Fallback 1 | Fallback 2 |
|---|---|---|
get_joint_associated_diseases_by_HPO_ID_list | Orphanet_search_diseases | PubMed phenotype search |
ClinVar_get_variant_details | gnomad_get_variant | VEP annotation |
GTEx_get_expression_summary | HPA_search_genes_by_query | Tissue-specific literature |
scripts/clinical_patterns.py - Clinical pattern lookup (syndromes, differentials, red flags, occupational exposures)npx claudepluginhub mims-harvard/tooluniverse --plugin tooluniverseSearches Orphanet, GenCC, ClinVar, and ClinicalTrials.gov for rare disease gene curation, novel gene discovery, and variant interpretation. Also supports drug repurposing for orphan diseases.
Queries the Monarch Initiative knowledge graph for disease-gene-phenotype associations across species, integrating OMIM, ORPHANET, HPO, ClinVar, and model organism databases. Use for rare disease gene discovery, phenotype mapping, and cross-species modeling.
Query the Monarch Initiative knowledge graph for disease-gene-phenotype associations across species. Integrates OMIM, ORPHANET, HPO, ClinVar, and model organism databases.