name: varcadd-pathogenicity description: Variant Scorer keywords:

• variant-interpretation
• CADD
• pathogenicity
• genomics
• prediction measurable_outcome: Return pathogenicity scores for a VCF of 1000 variants within 2 minutes, flagging top 1% deleterious hits. license: Non-Commercial metadata: author: Genome Medicine 2025 version: "1.0.0" compatibility:
• system: Python 3.9+ allowed-tools:
• run_shell_command
• read_file

varCADD (Variant Pathogenicity Predictor)

Genome-wide pathogenicity prediction leveraging standing variation data to improve accuracy over traditional CADD scores.

When to Use

• Variant Prioritization: Ranking candidate variants in rare disease cases.
• VUS Interpretation: Assessing variants of uncertain significance.
• Research: Annotating novel variants in population studies.

Core Capabilities

1. Score Generation: Calculate C-scores for SNVs and indels.
2. Annotation: Add functional context (conservation, protein domains).
3. Filtering: Identify likely pathogenic variants based on thresholds.

Workflow

1. Input: VCF file.
2. Annotate: Run varCADD model.
3. Filter: Keep variants with Score > X.
4. Output: Annotated VCF or ranked table.

Example Usage

User: "Score these variants from patient X."

Agent Action:

varcadd score --input patient.vcf --output scored.vcf