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MubasherMohammed
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clinical-variant-reporter

Classify germline variants from VCF files using ACMG/AMP 2015 criteria.

Updated May 10, 2026
Search Tags:#ACMG#variant classification#clinical genomics#pathogenicity#germline#secondary findings
One-click install
npx skills add https://github.com/MubasherMohammed/opencode-BioInfo --skill clinical-variant-reporter
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: clinical-variant-reporter
Source: https://github.com/MubasherMohammed/opencode-BioInfo/tree/main/python/skills/clinical-variant-reporter
Command: npx skills add https://github.com/MubasherMohammed/opencode-BioInfo --skill clinical-variant-reporter

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pysam, requests, pandas, matplotlib, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides automated, guideline-grade classification of germline variants from VCF/BCF files, offering accurate, evidence-based ACMG classifications and generating detailed clinical interpretation reports.

Core Features & Use Cases

  • ACMG/AMP 28-Criteria Evaluation: Assess each variant against a comprehensive evidence framework for ACMG classifications.
  • Clinical Grade Reports: Generate reports with per-variant evidence audit trails and ACMG SF v3.2 secondary findings screening.
  • Use Case: A geneticist can use this Skill to classify variants in a patient's VCF file, quickly identifying pathogenic or benign mutations, and generate a report with supporting evidence.

Quick Start

Use the clinical-variant-reporter skill to classify variants from the patient's VCF file and generate a report at the path '/output/report'.

Frequently Asked Questions about clinical-variant-reporter

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I classify germline variants in a VCF file using the ACMG 2015 criteria?▼

To classify germline variants, this Skill evaluates VCF or BCF files against the ACMG/AMP 2015 28-criteria evidence framework and generates a clinical-grade interpretation report with full evidence audit trails.

What is ACMG SF v3.2 secondary findings screening and how does it apply to variant classification?▼

ACMG SF v3.2 secondary findings screening evaluates germline variants for medically actionable secondary findings. This Skill automates that screening process alongside standard pathogenicity classification to identify relevant clinical mutations.

Can I use pysam and pandas to automate variant pathogenicity classification from VCF files?▼

Yes, this Skill requires Python 3.10+ with pysam and pandas to parse VCF/BCF files locally. It fetches annotation data from ClinVar, gnomAD, and VEP REST APIs to support automated pathogenicity classification.

Does this variant classification tool require external API access to ClinVar and gnomAD?▼

Yes, the Skill requires access to ClinVar, gnomAD, and VEP REST APIs to retrieve annotation data needed for evaluating the ACMG 28-criteria evidence framework and generating accurate clinical reports.

What's the best way to generate clinical-grade ACMG classification reports with evidence audit trails?▼

The best way is to process your VCF file through this Skill, which evaluates each variant against the 28 ACMG criteria and outputs a detailed report containing per-variant evidence audit trails at a specified output path.

Are there limitations when classifying somatic variants instead of germline variants with the ACMG framework?▼

Yes, a key limitation is that this Skill is designed specifically for germline variant classification using the ACMG/AMP 2015 framework. It is not intended for somatic variant classification workflows.

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