tooluniverse-structural-variant-analysis

name

tooluniverse-structural-variant-analysis

description

Structural variant (SV) clinical interpretation: deletions, duplications, inversions, translocations, complex rearrangements. Applies ACMG-adapted criteria with ClinGen HI/TS dosage scores, gnomAD frequencies, and ClinVar evidence. Produces 5-tier classification with explicit per-criterion evidence. Use for clinical genomics SV review, dosage-sensitivity assessment, breakpoint analysis, and CNV pathogenicity calls. Gene-dosage-driven reasoning.

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.

Structural Variant Analysis Workflow

Systematic analysis of structural variants (deletions, duplications, inversions, translocations, complex rearrangements) for clinical genomics interpretation using ACMG-adapted criteria.

LOOK UP DON'T GUESS - Always retrieve ClinGen HI/TS scores, gnomAD frequencies, and ClinVar evidence from tools. Do not infer dosage sensitivity from gene function alone.

KEY PRINCIPLES:

1. Report-first approach - Create SV_analysis_report.md FIRST, then populate progressively
2. ACMG-style classification - Pathogenic/Likely Pathogenic/VUS/Likely Benign/Benign with explicit evidence
3. Evidence grading - Grade all findings by confidence level (High/Moderate/Limited)
4. Dosage sensitivity critical - Gene dosage effects drive SV pathogenicity
5. Breakpoint precision matters - Exact gene disruption vs dosage-only effects
6. Population context essential - gnomAD SVs for frequency assessment
7. English-first queries - Always use English terms in tool calls. Respond in the user's language

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Triggers

Use this skill when users:

• Ask about structural variant interpretation
• Have CNV data from array or sequencing
• Ask "is this deletion/duplication pathogenic?"
• Need ACMG classification for SVs
• Want to assess gene dosage effects
• Ask about chromosomal rearrangements
• Have large-scale genomic alterations requiring interpretation

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SV Pathogenicity Reasoning (Start Here)

Before any tool call, apply this reasoning to frame the analysis:

SV pathogenicity depends on what the SV disrupts. A deletion removing an entire gene is likely pathogenic if the gene is haploinsufficient. A duplication is pathogenic if the gene is dosage-sensitive. An inversion is pathogenic only if it disrupts a coding region or regulatory element at the breakpoint.

Work through these questions in order:

1. What type is the SV, and what disruption mechanism does it cause?

• Deletion: loss of one copy. Pathogenic if any contained gene is haploinsufficient (ClinGen HI score 3, pLI >= 0.9). A deletion of a dosage-insensitive gene in a gene-dense region may be benign even if large.
• Duplication: gain of one copy. Pathogenic if any contained gene is dosage-sensitive (ClinGen TS score 3). Duplications can also disrupt gene regulation if tandem (disrupts reading frame at junction) or if they separate a gene from its enhancer.
• Inversion: no copy number change. Pathogenic only at the breakpoints: if one breakpoint falls within an exon (truncation) or separates a gene from its regulatory element. Inversions entirely within gene-poor, regulatory-poor regions are often benign.
• Translocation: pathogenic if a breakpoint disrupts a coding region or creates a pathogenic fusion gene. Balanced translocations in parents of affected children warrant special scrutiny.
• Complex rearrangements: assess each segment and each breakpoint independently.

2. Is the disrupted gene dosage-sensitive?

• ClinGen HI score 3 = definitive haploinsufficiency (deletion of this gene is pathogenic)
• ClinGen HI score 2 = likely haploinsufficient
• pLI >= 0.9 = strong LoF intolerance (supporting haploinsufficiency)
• ClinGen TS score 3 = definitive triplosensitivity (duplication is pathogenic)
• If no ClinGen data: use OMIM inheritance (autosomal dominant = often dosage-sensitive) as weaker evidence

3. Does the population frequency contextualize the SV?

• =1% frequency in gnomAD SV = BA1 (likely benign unless phenotype is extreme)

• <0.01% = supports pathogenicity (PM2)
• Present in unaffected parents = weak evidence against pathogenicity, but not conclusive

4. Is there clinical precedent?

• Identical SV in ClinVar as Pathogenic/Likely Pathogenic = strong evidence (PS1)
• De novo occurrence = strong evidence for pathogenicity (PS2)
• Phenotype match to known gene-disease association = supporting evidence (PP4)

Document this reasoning before computing the final score.

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Workflow Overview

Phase 1: SV IDENTITY & CLASSIFICATION
  Normalize coordinates (hg19/hg38), determine type (DEL/DUP/INV/TRA/CPX),
  calculate size, assess breakpoint precision

Phase 2: GENE CONTENT ANALYSIS
  Identify fully contained genes, partially disrupted genes (breakpoint within),
  flanking genes (within 1 Mb), annotate function and disease associations

Phase 3: DOSAGE SENSITIVITY ASSESSMENT
  ClinGen HI/TS scores, pLI scores, OMIM inheritance patterns,
  gene-disease validity levels

Phase 4: POPULATION FREQUENCY CONTEXT
  gnomAD SV database, ClinVar known SVs, DECIPHER patient cases,
  reciprocal overlap calculation (>=70% = same SV)

Phase 5: PATHOGENICITY SCORING
  Quantitative 0-10 scale: gene content (40%), dosage sensitivity (30%),
  population frequency (20%), clinical evidence (10%)

Phase 6: LITERATURE & CLINICAL EVIDENCE
  PubMed searches, DECIPHER cohort analysis, functional evidence

Phase 7: ACMG-ADAPTED CLASSIFICATION
  Apply SV-specific evidence codes, calculate final classification,
  generate clinical recommendations

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Phase 1: SV Identity & Classification

Goal: Standardize SV notation and classify type.

Capture: chromosome(s), coordinates (start/end in hg19/hg38), SV size, SV type (DEL/DUP/INV/TRA/CPX), breakpoint precision, inheritance pattern (de novo/inherited/unknown).

For SV type definitions, scoring tables, and ACMG code details, see CLASSIFICATION_GUIDE.md.

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Phase 2: Gene Content Analysis

Goal: Annotate all genes affected by the SV.

Tools:

• ensembl_lookup_gene - gene structure, coordinates, exons
• NCBIGene_search - official symbol, aliases, description
• GO_get_term_details - biological process, molecular function
• OMIM_search, OMIM_get_entry - disease associations, inheritance
• DisGeNET_search_gene - gene-disease association scores

Classify genes as: fully contained (entire gene in SV), partially disrupted (breakpoint within gene), or flanking (within 1 Mb of breakpoints).

For implementation pseudocode, see ANALYSIS_PROCEDURES.md Phase 2.

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Phase 3: Dosage Sensitivity Assessment

Goal: Determine if affected genes are dosage-sensitive.

Tools:

• ClinGen_search_dosage_sensitivity - HI/TS scores (0-3, gold standard)
• ClinGen_search_gene_validity - gene-disease validity level
• gnomad_search_variants - pLI scores for LoF intolerance
• OMIM_get_entry - inheritance pattern (AD suggests dosage sensitivity)

Interpret scores using the reasoning above. ClinGen HI/TS score 3 = definitive; score 2 = likely; score 1 = little evidence; score 0 = no evidence. Do not equate AD inheritance with haploinsufficiency without ClinGen support.

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Phase 4: Population Frequency Context

Goal: Determine if SV is common (likely benign) or rare (supports pathogenicity).

Tools:

• gnomad_search_variants - population SV frequencies
• ClinVar_search_variants - known pathogenic/benign SVs
• ClinGen_search_dosage_sensitivity - patient SVs with phenotypes

Use >=70% reciprocal overlap to define "same" SV for comparison. A frequency >=1% triggers BA1 unless there is very strong clinical evidence to override.

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Phase 5: Pathogenicity Scoring

Goal: Quantitative pathogenicity assessment on 0-10 scale.

Four components weighted: gene content (40%), dosage sensitivity (30%), population frequency (20%), clinical evidence (10%).

Score mapping: 9-10 = Pathogenic, 7-8 = Likely Pathogenic, 4-6 = VUS, 2-3 = Likely Benign, 0-1 = Benign.

For detailed scoring breakdowns and implementation, see CLASSIFICATION_GUIDE.md and ANALYSIS_PROCEDURES.md Phase 5.

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Phase 6: Literature & Clinical Evidence

Goal: Find case reports, functional studies, and clinical validation.

Tools:

• PubMed_search_articles - peer-reviewed literature
• EuropePMC_search_articles - additional coverage
• ClinGen_search_dosage_sensitivity - patient case database

Search strategies: gene-specific dosage sensitivity papers, SV-specific case reports, phenotype-gene associations. See ANALYSIS_PROCEDURES.md Phase 6.

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Phase 7: ACMG-Adapted Classification

Goal: Apply ACMG/ClinGen criteria adapted for SVs and generate a final classification with explicit evidence summary.

The LLM knows the ACMG criteria codes and combination rules. Apply them to the evidence gathered in Phases 1-6. Key points to verify with tool data:

• PVS1 applies to deletions of genes with ClinGen HI score >= 2 or pLI >= 0.9
• PS2 requires confirmed de novo status (check parental genotypes if available)
• PM2 requires absence from population databases at >=70% reciprocal overlap

For complete evidence code tables and classification algorithm, see CLASSIFICATION_GUIDE.md.

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Output

Create report using the template in REPORT_TEMPLATE.md. Name files as:

SV_analysis_[TYPE]_chr[CHR]_[START]_[END]_[GENES].md

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Required Tools Reference

• ClinGen_search_dosage_sensitivity - HI/TS scores (required for all deletions/duplications)
• ClinGen_search_gene_validity - gene-disease validity (required)
• ClinVar_search_variants - known pathogenic/benign SVs (required)
• ensembl_lookup_gene - gene coordinates, structure (required)
• OMIM_search, OMIM_get_entry - gene-disease associations (required)
• gnomad_search_variants - population frequency and pLI (required)
• DisGeNET_search_gene - additional disease associations (recommended)
• PubMed_search_articles - literature evidence (recommended)
• GO_get_term_details - gene function (supporting)

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When NOT to Use This Skill

• Single nucleotide variants (SNVs) - Use tooluniverse-variant-interpretation
• Small indels (<50 bp) - Use variant interpretation skill
• Somatic variants in cancer - Different framework needed
• Mitochondrial variants - Specialized interpretation required
• Repeat expansions - Different mechanism

Use this skill for structural variants >=50 bp requiring dosage sensitivity assessment and ACMG-adapted classification.

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Reference Files

• EXAMPLES.md - Sample SV interpretations with worked examples
• CLASSIFICATION_GUIDE.md - ACMG criteria, scoring system, evidence codes, special scenarios, clinical recommendations
• REPORT_TEMPLATE.md - Full report template with section structure and file naming
• ANALYSIS_PROCEDURES.md - Detailed implementation pseudocode for each phase

External References

• ClinGen Dosage Sensitivity Map: https://www.ncbi.nlm.nih.gov/projects/dbvar/clingen/
• ACMG SV Guidelines: Riggs et al., Genet Med 2020 (PMID: 31690835)
• tooluniverse-variant-interpretation - For SNVs and small indels