# Variant Pathogenicity Predictor

> Integrate REVEL, CADD, PolyPhen scores to predict variant pathogenicity

- Skill: `dvcrn/variant-pathogenicity-predictor` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add dvcrn/variant-pathogenicity-predictor`
- Raw SKILL.md: https://api.skillmd.com/api/skills/dvcrn/variant-pathogenicity-predictor/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: dvcrn (https://skillmd.com/u/dvcrn)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/dvcrn/variant-pathogenicity-predictor

---


# Variant Pathogenicity Predictor

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

## Usage

```bash
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 Indicator | Assessment | Level |
|----------------|------------|-------|
| Code Execution | Python/R scripts executed locally | Medium |
| Network Access | No external API calls | Low |
| File System Access | Read input files, write output files | Medium |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Output files saved to workspace | Low |

## 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