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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.
disable-model-invocation
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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:
Report-first approach - Create SV_analysis_report.md FIRST, then populate progressively
ACMG-style classification - Pathogenic/Likely Pathogenic/VUS/Likely Benign/Benign with explicit evidence
Evidence grading - Grade all findings by confidence level (High/Moderate/Limited)
Population context essential - gnomAD SVs for frequency assessment
English-first queries - Always use English terms in tool calls. Respond in the user's language
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
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.
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.
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.
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%).
