tooluniverse-variant-interpretation

name

tooluniverse-variant-interpretation

description

Systematic clinical variant interpretation from raw variant calls to ACMG-classified recommendations with structural impact analysis. Aggregates evidence from ClinVar, gnomAD, CIViC, UniProt, and PDB across ACMG criteria. Produces pathogenicity scores (0-100), clinical recommendations, and treatment implications. Use when interpreting genetic variants, classifying variants of uncertain significance (VUS), performing ACMG variant classification, or translating variant calls to clinical actionability.

Clinical Variant Interpreter

Systematic variant interpretation using ToolUniverse — from raw variant calls to ACMG-classified clinical recommendations with structural impact analysis.

Key Principles

1. ACMG-Guided Classification - Follow ACMG/AMP 2015 guidelines with explicit evidence codes
2. Structural Evidence Integration - Use AlphaFold2 for novel structural impact analysis
3. Population Context - gnomAD frequencies with ancestry-specific data
4. Gene-Disease Validity - ClinGen curation status for clinical relevance
5. Actionable Output - Clear recommendations, not just classifications
6. English-first queries - Always use English terms in tool calls

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Triggers

Use when users:

• Ask about variant interpretation, classification, or pathogenicity
• Have VCF data needing clinical annotation
• Need ACMG classification for variants (especially VUS)
• Want structural impact analysis for missense variants

NOT for: Structural variants/CNVs → tooluniverse-structural-variant-analysis; Variant calling from BAM → tooluniverse-variant-analysis

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Workflow (6 Phases)

Phase 1: Variant Identity & Normalization

Standardize notation (HGVS), map to gene/transcript/protein, determine consequence type.

Tool	Purpose
myvariant_query	Variant annotations from MyVariant.info (dbSNP, ClinVar, gnomAD)
Ensembl_get_variant_info	Variant effect predictor data
NCBI_gene_search	Gene information, RefSeq transcripts

Capture: HGVS (c. and p.), gene symbol, Ensembl ID, transcript (MANE Select), consequence, amino acid change, exon/intron location.

Phase 2: Clinical Database Queries

Tool	Purpose	Key Data
clinvar_search	Existing classifications	Classification, review status, conditions
gnomad_search	Population frequency	Overall AF, ancestry-specific AFs, homozygotes
OMIM_search + OMIM_get_entry	Gene-disease	Inheritance pattern, phenotypes
ClinGen_search_gene_validity	Gene curation	Gene-disease validity level
ClinGen_search_dosage_sensitivity	Dosage sensitivity	HI/TS scores
COSMIC_search_mutations	Somatic context	Cancer frequency, hotspot status
DisGeNET_search_gene	Gene-disease associations	Evidence scores

gnomAD frequency interpretation:

• Absent (0) → PM2 (Supporting Pathogenic)
• <0.01% → Rare, consistent with pathogenicity
• 0.01-0.1% → Check gene/disease prevalence
• >1% → BA1 (Stand-alone Benign)

Phase 3: Computational Predictions

Tool	Purpose	Threshold
myvariant_query (contains SIFT/PolyPhen/CADD)	Damaging predictions	CADD ≥25 = likely deleterious
SpliceAI (via myvariant or Ensembl)	Splice impact	Score ≥0.5 = high splice impact
Conservation (via Ensembl)	Cross-species alignment	PhyloP, GERP scores

PP3 (Supporting Pathogenic): ≥3 concordant computational predictors agree "damaging" BP4 (Supporting Benign): ≥3 concordant predictors agree "tolerated"

Phase 4: Structural Analysis (for VUS/novel missense)

Tool	Purpose
AlphaFold_get_prediction	Predicted protein structure
PDB_search	Experimental crystal structures
UniProt_search	Domain/feature annotations, active sites
InterPro_search	Protein family/domain classification

Assess: Is residue buried/surface? Domain/active site? Secondary structure? pLDDT confidence (>90 = very high, 70-90 = high, 50-70 = moderate, <50 = disordered)?

PM1: Apply if variant in established functional domain without benign variation.

Phase 5: Literature Evidence

Tool	Purpose
PubMed_search_articles	Functional studies, case reports (returns plain list)
EuropePMC_search_articles	Broader literature
CIViC_search	Cancer clinical evidence (if oncology)

PS3 (Strong): Well-established functional study shows damaging effect BS3 (Strong): Well-established functional study shows no effect

Phase 6: ACMG Classification

Key pathogenic evidence codes:

Code	Strength	Criteria
PVS1	Very Strong	LOF in gene where LOF is disease mechanism
PS1	Strong	Same amino acid change as established pathogenic
PS3	Strong	Functional studies confirm damaging
PM1	Moderate	In critical functional domain
PM2	Moderate	Absent from gnomAD
PP3	Supporting	Computational predictions concordant "damaging"

Key benign evidence codes:

Code	Strength	Criteria
BA1	Stand-alone	gnomAD AF >1%
BS1	Strong	gnomAD AF higher than expected for disease
BS3	Strong	Functional study shows no effect
BP4	Supporting	Computational predictions concordant "tolerated"

Classification rules:

• Pathogenic: 1 Very Strong + 1 Strong, OR 2 Strong + ≥1 Moderate
• Likely Pathogenic: 1 Very Strong + 1 Moderate, OR 1 Strong + 2 Moderate
• VUS: Criteria insufficient for either direction
• Likely Benign: 1 Strong + 1 Supporting benign
• Benign: 1 Stand-alone benign, OR ≥2 Strong benign

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Special Scenarios

Novel Missense VUS: Phase 4 structural analysis critical → check if other pathogenic variants at same residue → AlphaFold2 → buried/surface? active site? conservation?

Truncating Variant: Check LOF mechanism → NMD escape (last exon)? → ClinGen LOF curation → PVS1 strength depends on LOF mechanism

Splice Variant: SpliceAI scores → canonical splice distance → in-frame skipping? → cryptic splice activation?

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Report Template (9 sections)

1. Variant Identity (HGVS, gene, transcript, consequence)
2. Population Data (gnomAD frequencies, ancestry breakdown)
3. Clinical Database Evidence (ClinVar, OMIM, ClinGen)
4. Computational Predictions (SIFT, PolyPhen, CADD, SpliceAI)
5. Structural Analysis (AlphaFold2/PDB, domain impact, confidence)
6. Literature Evidence (functional studies, case reports)
7. ACMG Classification (evidence codes, final classification + rationale)
8. Clinical Recommendations (actionable: diagnostic, therapeutic, family screening)
9. Limitations & Uncertainties

Minimum requirements: gnomAD overall + ≥3 ancestry groups, ≥3 computational predictors, ≥2 literature search strategies, all applicable ACMG codes listed.

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Extended Reference: Full Python implementations, detailed tool parameter tables, NVIDIA NIM integration, example reports, and special scenario workflows are in REFERENCE.md.