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Variant Pathogenicity Predictor

v0.1.0

Integrate REVEL, CADD, PolyPhen scores to predict variant pathogenicity

0· 278· 1 versions· 0 current· 0 all-time· Updated 17h ago· MIT-0

Install

openclaw skills install variant-pathogenicity-predictor

Variant Pathogenicity Predictor

Integrate REVEL, CADD, PolyPhen and other scores to predict variant pathogenicity.

Usage

python scripts/main.py --variant "chr17:43094692:G:A" --gene "BRCA1"
python scripts/main.py --vcf variants.vcf --output report.json

Parameters

  • --variant: Variant in format chr:pos:ref:alt
  • --vcf: VCF file with variants
  • --gene: Gene symbol
  • --scores: Prediction scores to use (REVEL,CADD,PolyPhen)

Integrated Scores

  • REVEL (Rare Exome Variant Ensemble Learner)
  • CADD (Combined Annotation Dependent Depletion)
  • PolyPhen-2 (Polymorphism Phenotyping)
  • SIFT (Sorting Intolerant From Tolerant)
  • MutationTaster

Output

  • Pathogenicity classification
  • ACMG guideline interpretation
  • Individual score breakdown
  • Confidence assessment

Risk Assessment

Risk IndicatorAssessmentLevel
Code ExecutionPython/R scripts executed locallyMedium
Network AccessNo external API callsLow
File System AccessRead input files, write output filesMedium
Instruction TamperingStandard prompt guidelinesLow
Data ExposureOutput files saved to workspaceLow

Security Checklist

  • No hardcoded credentials or API keys
  • No unauthorized file system access (../)
  • Output does not expose sensitive information
  • Prompt injection protections in place
  • Input file paths validated (no ../ traversal)
  • Output directory restricted to workspace
  • Script execution in sandboxed environment
  • Error messages sanitized (no stack traces exposed)
  • Dependencies audited

Prerequisites

No additional Python packages required.

Evaluation Criteria

Success Metrics

  • Successfully executes main functionality
  • Output meets quality standards
  • Handles edge cases gracefully
  • Performance is acceptable

Test Cases

  1. Basic Functionality: Standard input → Expected output
  2. Edge Case: Invalid input → Graceful error handling
  3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

  • Current Stage: Draft
  • Next Review Date: 2026-03-06
  • Known Issues: None
  • Planned Improvements:
    • Performance optimization
    • Additional feature support

Version tags

latestvk978t1fr3fyxmeejxnhjrys1qx82vgzw