Structural Variant Analysis Workflow
Systematic analysis of structural variants (deletions, duplications, inversions, translocations, complex rearrangements) for clinical genomics interpretation using ACMG-adapted criteria.
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 (★★★/★★☆/★☆☆)
- Dosage sensitivity critical - Gene dosage effects drive SV pathogenicity
- Breakpoint precision matters - Exact gene disruption vs dosage-only effects
- Population context essential - gnomAD SVs for frequency assessment
- English-first queries - Always use English terms in tool calls
Triggers
Use this skill when users:
- Ask about structural variant interpretation or CNV data
- Ask "is this deletion/duplication pathogenic?"
- Need ACMG classification for SVs or gene dosage assessment
- Have chromosomal rearrangements requiring interpretation
NOT for: SNV/indel interpretation → tooluniverse-variant-interpretation; gene enrichment → tooluniverse-gene-enrichment
Workflow (7 Phases)
Phase 1: SV Identity & Classification
Normalize coordinates (hg19/hg38), determine type (DEL/DUP/INV/TRA/CPX), calculate size, assess breakpoint precision.
| SV Type |
Abbreviation |
Molecular Effect |
| Deletion |
DEL |
Haploinsufficiency, gene disruption |
| Duplication |
DUP |
Triplosensitivity, dosage imbalance |
| Inversion |
INV |
Gene disruption at breakpoints, position effects |
| Translocation |
TRA |
Gene fusions, disruption, position effects |
| Complex |
CPX |
Variable effects |
Phase 2: Gene Content Analysis
Identify genes fully contained in SV and genes with breakpoints (disrupted). Annotate function and disease associations.
| Tool |
Purpose |
Ensembl_lookup_gene |
Gene structure, coordinates, exons |
NCBI_gene_search |
Official symbol, description |
OMIM_search + OMIM_get_entry |
Disease associations, inheritance |
DisGeNET_search_gene |
Gene-disease evidence scores |
Gene_Ontology_get_term_info |
Biological process, molecular function |
Phase 3: Dosage Sensitivity Assessment
from tooluniverse import ToolUniverse
tu = ToolUniverse(use_cache=True); tu.load_tools()
# ClinGen dosage (gold standard)
clingen = tu.tools.ClinGen_search_dosage_sensitivity(gene="KANSL1")
# -> hi_score: 3 = Sufficient evidence for HI
# ClinGen gene validity
validity = tu.tools.ClinGen_search_gene_validity(gene="KANSL1")
# -> Classification: Definitive
# gnomAD constraint (pLI)
gnomad = tu.tools.gnomad_get_gene_constraints(gene_symbol="KANSL1")
# -> pLI close to 1.0 = loss-of-function intolerant
# OMIM inheritance
omim = tu.tools.OMIM_search(operation="search", query="KANSL1", limit=3)
Evidence grading: HI/TS score=3 + Definitive validity = ★★★ | Score 2-3 = ★★☆ | Otherwise = ★☆☆
Phase 4: Population Frequency Context
| Tool |
Purpose |
gnomad_search |
Population SV frequencies, overlapping SVs |
ClinVar_search_variants |
Known pathogenic/benign SVs (chromosome, start, stop, variant_type) |
DECIPHER_search |
Patient SVs with phenotypes, case reports |
ACMG frequency codes:
- ≥1% in gnomAD SVs → BA1 (Stand-alone Benign)
- 0.1-1% → BS1 (Strong Benign)
- <0.01% or absent → PM2 (Supporting Pathogenic)
Reciprocal overlap: min(overlap/SV_A_length, overlap/SV_B_length) ≥70% = "same" SV
Phase 5: Pathogenicity Scoring (0-10)
| Component |
Weight |
Max Points |
| Gene content |
40% |
4 pts: dosage-sensitive gene disrupted; 3: disease gene fully contained; 2: OMIM gene; 1: any gene |
| Dosage sensitivity |
30% |
3 pts: HI/TS score=3 + Definitive validity; 2: score 2-3; 1: predicted only |
| Population frequency |
20% |
2 pts: absent from gnomAD+DGV; 1: rare (<0.01%); 0: common |
| Clinical match |
10% |
1 pt: phenotype consistent + literature support |
Score interpretation:
- 9-10: Pathogenic | 7-8.9: Likely Pathogenic | 4-6.9: VUS | 2-3.9: Likely Benign | 0-1.9: Benign
Phase 6: Literature & Clinical Evidence
| Tool |
Purpose |
PubMed_search_articles |
Similar SVs, gene disruption studies (returns plain list) |
DECIPHER_search |
Developmental disorder cases with overlapping SVs |
EuropePMC_search_articles |
Broader literature search |
Phase 7: ACMG-Adapted Classification
Key pathogenic codes for SVs:
- PVS1: Gene disruption of established HI gene (Very Strong)
- PS1: Same SV as known pathogenic in ClinVar (Strong)
- PS3: Functional studies confirm dosage sensitivity (Strong)
- PM2: Absent from population databases (Moderate)
- PP4: Patient phenotype matches gene's disease (Supporting)
Key benign codes:
- BA1: ≥1% frequency in gnomAD SVs (Stand-alone)
- BS1: 0.1-1% frequency (Strong)
- BP1: No known disease genes in region (Supporting)
Classification: 1 Very Strong + 1 Strong = Pathogenic | 1 Very Strong + 1-2 Moderate = Likely Pathogenic | Contradictory = VUS
Report Template
| Section |
Content |
| 1. SV Summary |
Type, coordinates, size, breakpoint precision |
| 2. Gene Content |
Fully contained genes, disrupted genes, regulatory elements |
| 3. Dosage Sensitivity |
ClinGen HI/TS scores, pLI, validity level per gene |
| 4. Population Frequency |
gnomAD/ClinVar/DECIPHER overlaps, ACMG codes |
| 5. Pathogenicity Score |
0-10 score with component breakdown |
| 6. Literature Evidence |
Key publications, DECIPHER cases, functional evidence |
| 7. ACMG Classification |
Evidence codes applied, final classification + rationale |
| 8. Clinical Recommendations |
Immediate actions, further investigation, genetic counseling |
Extended Reference: Full Python implementations for each phase, detailed ACMG criteria tables, example reports, and edge case handling are in REFERENCE.md.
1---2name: tooluniverse-structural-variant-analysis3description: Comprehensive structural variant (SV) analysis skill for clinical genomics. Classifies SVs (deletions, duplications, inversions, translocations), assesses pathogenicity using ACMG-adapted criteria, evaluates gene disruption and dosage sensitivity, and provides clinical interpretation with evidence grading. Use when analyzing CNVs, large deletions/duplications, chromosomal rearrangements, or any structural variants requiring clinical interpretation.4---56# Structural Variant Analysis Workflow78Systematic analysis of structural variants (deletions, duplications, inversions, translocations, complex rearrangements) for clinical genomics interpretation using ACMG-adapted criteria.910**KEY PRINCIPLES**:111. **Report-first approach** - Create SV_analysis_report.md FIRST, then populate progressively122. **ACMG-style classification** - Pathogenic/Likely Pathogenic/VUS/Likely Benign/Benign with explicit evidence133. **Evidence grading** - Grade all findings by confidence level (★★★/★★☆/★☆☆)144. **Dosage sensitivity critical** - Gene dosage effects drive SV pathogenicity155. **Breakpoint precision matters** - Exact gene disruption vs dosage-only effects166. **Population context essential** - gnomAD SVs for frequency assessment177. **English-first queries** - Always use English terms in tool calls1819---2021## Triggers2223Use this skill when users:24- Ask about structural variant interpretation or CNV data25- Ask "is this deletion/duplication pathogenic?"26- Need ACMG classification for SVs or gene dosage assessment27- Have chromosomal rearrangements requiring interpretation2829**NOT for**: SNV/indel interpretation → `tooluniverse-variant-interpretation`; gene enrichment → `tooluniverse-gene-enrichment`3031---3233## Workflow (7 Phases)3435### Phase 1: SV Identity & Classification3637Normalize coordinates (hg19/hg38), determine type (DEL/DUP/INV/TRA/CPX), calculate size, assess breakpoint precision.3839| SV Type | Abbreviation | Molecular Effect |40|---------|-------------|------------------|41| Deletion | DEL | Haploinsufficiency, gene disruption |42| Duplication | DUP | Triplosensitivity, dosage imbalance |43| Inversion | INV | Gene disruption at breakpoints, position effects |44| Translocation | TRA | Gene fusions, disruption, position effects |45| Complex | CPX | Variable effects |4647### Phase 2: Gene Content Analysis4849Identify genes fully contained in SV and genes with breakpoints (disrupted). Annotate function and disease associations.5051| Tool | Purpose |52|------|---------|53| `Ensembl_lookup_gene` | Gene structure, coordinates, exons |54| `NCBI_gene_search` | Official symbol, description |55| `OMIM_search` + `OMIM_get_entry` | Disease associations, inheritance |56| `DisGeNET_search_gene` | Gene-disease evidence scores |57| `Gene_Ontology_get_term_info` | Biological process, molecular function |5859### Phase 3: Dosage Sensitivity Assessment6061```python62from tooluniverse import ToolUniverse63tu = ToolUniverse(use_cache=True); tu.load_tools()6465# ClinGen dosage (gold standard)66clingen = tu.tools.ClinGen_search_dosage_sensitivity(gene="KANSL1")67# -> hi_score: 3 = Sufficient evidence for HI6869# ClinGen gene validity70validity = tu.tools.ClinGen_search_gene_validity(gene="KANSL1")71# -> Classification: Definitive7273# gnomAD constraint (pLI)74gnomad = tu.tools.gnomad_get_gene_constraints(gene_symbol="KANSL1")75# -> pLI close to 1.0 = loss-of-function intolerant7677# OMIM inheritance78omim = tu.tools.OMIM_search(operation="search", query="KANSL1", limit=3)79```8081**Evidence grading**: HI/TS score=3 + Definitive validity = ★★★ | Score 2-3 = ★★☆ | Otherwise = ★☆☆8283### Phase 4: Population Frequency Context8485| Tool | Purpose |86|------|---------|87| `gnomad_search` | Population SV frequencies, overlapping SVs |88| `ClinVar_search_variants` | Known pathogenic/benign SVs (chromosome, start, stop, variant_type) |89| `DECIPHER_search` | Patient SVs with phenotypes, case reports |9091**ACMG frequency codes**:92- ≥1% in gnomAD SVs → BA1 (Stand-alone Benign)93- 0.1-1% → BS1 (Strong Benign)94- <0.01% or absent → PM2 (Supporting Pathogenic)9596**Reciprocal overlap**: min(overlap/SV_A_length, overlap/SV_B_length) ≥70% = "same" SV9798### Phase 5: Pathogenicity Scoring (0-10)99100| Component | Weight | Max Points |101|-----------|--------|-----------|102| Gene content | 40% | 4 pts: dosage-sensitive gene disrupted; 3: disease gene fully contained; 2: OMIM gene; 1: any gene |103| Dosage sensitivity | 30% | 3 pts: HI/TS score=3 + Definitive validity; 2: score 2-3; 1: predicted only |104| Population frequency | 20% | 2 pts: absent from gnomAD+DGV; 1: rare (<0.01%); 0: common |105| Clinical match | 10% | 1 pt: phenotype consistent + literature support |106107**Score interpretation**:108- **9-10**: Pathogenic | **7-8.9**: Likely Pathogenic | **4-6.9**: VUS | **2-3.9**: Likely Benign | **0-1.9**: Benign109110### Phase 6: Literature & Clinical Evidence111112| Tool | Purpose |113|------|---------|114| `PubMed_search_articles` | Similar SVs, gene disruption studies (returns plain list) |115| `DECIPHER_search` | Developmental disorder cases with overlapping SVs |116| `EuropePMC_search_articles` | Broader literature search |117118### Phase 7: ACMG-Adapted Classification119120**Key pathogenic codes for SVs**:121- PVS1: Gene disruption of established HI gene (Very Strong)122- PS1: Same SV as known pathogenic in ClinVar (Strong)123- PS3: Functional studies confirm dosage sensitivity (Strong)124- PM2: Absent from population databases (Moderate)125- PP4: Patient phenotype matches gene's disease (Supporting)126127**Key benign codes**:128- BA1: ≥1% frequency in gnomAD SVs (Stand-alone)129- BS1: 0.1-1% frequency (Strong)130- BP1: No known disease genes in region (Supporting)131132**Classification**: 1 Very Strong + 1 Strong = Pathogenic | 1 Very Strong + 1-2 Moderate = Likely Pathogenic | Contradictory = VUS133134---135136## Report Template137138| Section | Content |139|---------|---------|140| 1. SV Summary | Type, coordinates, size, breakpoint precision |141| 2. Gene Content | Fully contained genes, disrupted genes, regulatory elements |142| 3. Dosage Sensitivity | ClinGen HI/TS scores, pLI, validity level per gene |143| 4. Population Frequency | gnomAD/ClinVar/DECIPHER overlaps, ACMG codes |144| 5. Pathogenicity Score | 0-10 score with component breakdown |145| 6. Literature Evidence | Key publications, DECIPHER cases, functional evidence |146| 7. ACMG Classification | Evidence codes applied, final classification + rationale |147| 8. Clinical Recommendations | Immediate actions, further investigation, genetic counseling |148149---150151> **Extended Reference**: Full Python implementations for each phase, detailed ACMG criteria tables, example reports, and edge case handling are in `REFERENCE.md`.
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