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tooluniverse-structural-variant-analysis
维护者 FreedomIntelligence · 最近更新 2026年4月1日
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 r….
原始来源
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/tooluniverse-structural-variant-analysis
- 维护者
- FreedomIntelligence
- 许可
- MIT
- 最近更新
- 2026年4月1日
技能摘要
来自 SKILL.md 的关键信息
核心说明
- Systematic analysis of structural variants (deletions,duplications,inversions,translocations,complex rearrangements) ,用于 clinical genomics interpretation ,使用 ACMG-adapted criteria。
- KEY PRINCIPLES:1. Report-first approach - Create SV_analysis_report.md FIRST,then populate progressively 2. ACMG-style 分类 - Pathogenic/Likely Pathogenic/VUS/Likely Benign/Benign ,支持 explicit evidence 3. Evidence grading - Grade all findings by confidence level (★★★/★★☆/★☆☆) 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 ,用于 frequency assessment 7. English-first queries - Always use English terms in tool calls (gene names,disease names),even if user writes in another language. Only try original-language terms as fallback. Respond in user's language。
- Generated:[Date] | Analyst:ToolUniverse SV Interpreter。
原始文档
SKILL.md 摘录
Problem This Skill Solves
Structural variants (SVs) present unique interpretation challenges:
- Complex molecular consequences - SVs can cause gene dosage changes, gene disruption, gene fusions, position effects
- Size matters - Pathogenicity depends on size, gene content, and breakpoint precision
- Limited databases - Fewer curated SVs in ClinVar compared to SNVs
- Dosage sensitivity - Haploinsufficiency and triplosensitivity are critical but gene-specific
- Population frequency - Large benign CNVs are common; distinguishing pathogenic from benign is challenging
This skill provides: A systematic workflow integrating SV classification, gene content analysis, dosage sensitivity assessment, population frequencies, and ACMG-adapted criteria into clinically actionable interpretations.
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
Phase 1: SV Identity & Classification
Goal: Standardize SV notation and classify type
SV Types:
| Type | Abbreviation | Description | Molecular Effect |
|---|---|---|---|
| Deletion | DEL | Loss of genomic segment | Haploinsufficiency, gene disruption |
| Duplication | DUP | Gain of genomic segment | Triplosensitivity, gene dosage imbalance |
| Inversion | INV | Segment flipped in orientation | Gene disruption at breakpoints, position effects |
| Translocation | TRA | Segment moved to different chromosome | Gene fusions, disruption, position effects |
| Complex | CPX | Multiple rearrangement types | Variable effects |
Key Information to Capture:
- Chromosome(s) involved
- Coordinates (start, end) in hg19/hg38
- SV size (bp or Mb)
- SV type (DEL/DUP/INV/TRA/CPX)
- Breakpoint precision (±50bp, ±1kb, etc.)
- Inheritance pattern (de novo, inherited, unknown)
Example:
适用场景
- 适合在analyzing CNVs,large deletions/duplications,chromosomal rearrangements,或 any structural variants requiring clinical interpretation时使用。
不适用场景
- Do not rely on this catalog entry alone ,用于 installation 或 maintenance details。
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