varcadd-pathogenicity

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