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Variant Pathogenicity Predictor

Integrate REVEL, CADD, PolyPhen scores to predict variant pathogenicity
整合REVEL、CADD、PolyPhen评分预测变异致病性
ec-cyber258
数据分析 clawhub v0.1.0 1 版本 100000 Key: 无需
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概述

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

版本历史

共 1 个版本

  • v0.1.0 当前
    2026-03-19 17:31 安全 安全

安全检测

腾讯云安全 (Keen)

安全,无风险
查看报告

腾讯云安全 (Sanbu)

安全,无风险
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