majiayu000 ---name: variant-interpretation-acmg description: Classifies genetic variants according to ACMG (American College of Medical Genetics) guidelines. keywords:
- acmg
- genomics
- variant-classification
- precision-medicine
- genetics measurable_outcome: Correctly classifies >95% of variants when provided with accurate ACMG evidence codes. license: MIT metadata: author: AI Group version: "1.0.0" compatibility:
- system: Python 3.10+ allowed-tools:
- run_shell_command
- read_file ---"
Variant Interpretation (ACMG)
The Variant Interpretation Skill automates the classification of genetic variants (Pathogenic, Benign, VUS) using a rules-based engine derived from ACMG guidelines.
When to Use This Skill
- When analyzing a VCF file for clinical reporting.
- To determine the clinical significance of a specific mutation (e.g., BRCA1 c.123A>G).
- To aggregate evidence (population freq, computational predictions) into a final verdict.
Core Capabilities
- Rule Scoring: Applies codes like PVS1 (Null variant), PM2 (Rare), PP3 (In silico).
- Classification: Combines scores to reach a verdict (Pathogenic, Likely Pathogenic, VUS, etc.).
- Explanation: Provides the logic/evidence used for the classification.
Workflow
- Input: Variant details (Gene, HGVS, Consequence) or Evidence codes directly.
- Process: Sums weights of applied ACMG criteria.
- Output: Final classification and score breakdown.
Example Usage
User: "Classify a variant with evidence PVS1 and PM2."
Agent Action:
python3 Skills/Genomics/Variant_Interpretation/acmg_classifier.py \
--evidence "PVS1,PM2"