equity-scorer

Compute HEIM diversity and equity metrics from VCF or ancestry data.

Updated May 10, 2026

Search Tags:#health equity #ancestry analysis #genetic diversity #HEIM #VCF parsing

Ready to run

npx skills add https://github.com/MubasherMohammed/opencode-BioInfo --skill equity-scorer-mubashermohammed

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: equity-scorer
Source: https://github.com/MubasherMohammed/opencode-BioInfo/tree/main/python/skills/equity-scorer
Command: npx skills add https://github.com/MubasherMohammed/opencode-BioInfo --skill equity-scorer-mubashermohammed

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires biopython, pandas, scikit-learn, matplotlib, numpy, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill computes HEIM (Health Equity Index for Minorities) metrics from genomic data, helping to quantify and visualize diversity and health equity across populations.

Core Features & Use Cases

Diversity Metrics: Compute heterozygosity, FST, and PCA plots.
HEIM Equity Score: Generate a composite score that measures representation equity across populations.
Ancestry Distribution: Summarize and visualize the ancestry composition of a dataset.
Markdown Report: Generate a full analysis report with tables, figures, methods, and reproducibility block.
Input Formats: Supports VCF and ancestry CSV files.
Use Case: For a biobank study, you can use this Skill to understand the diversity and equity of the genomic dataset by analyzing heterozygosity, FST, and PCA plots, and generating a HEIM score.

Quick Start

Run the equity-scorer skill with a VCF file: equity-scorer /path/to/vcf/file.vcf.

Frequently Asked Questions about equity-scorer

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

FAQPage Schema

How do I calculate HEIM health equity metrics from VCF files?▼

To calculate HEIM health equity metrics from VCF files, you parse genomic data to compute heterozygosity, FST, and PCA plots, generating a composite score that quantifies representation equity across populations.

What is a HEIM diversity score and when do I need it for genetic data analysis?▼

A HEIM diversity score is a composite metric quantifying health equity and genetic diversity across populations. You need it for biobank studies or bioinformatics research to evaluate representation equity in genomic datasets.

Can I use ancestry CSV files instead of VCF for ancestry distribution analysis?▼

Yes, you can use ancestry CSV files instead of VCF for ancestry distribution analysis. The tool supports both input formats, allowing you to summarize and visualize the ancestry composition of your dataset.

Do I need biopython and scikit-learn to compute FST and heterozygosity metrics?▼

Yes, you need biopython, scikit-learn, pandas, numpy, and matplotlib installed. These Python libraries handle VCF parsing, data analysis, PCA computation, and visualization for the diversity and equity metrics.

What is the best way to visualize genetic diversity across populations using Python?▼

The best way to visualize genetic diversity across populations is by generating PCA plots and ancestry distribution summaries using matplotlib, accompanied by a full markdown report with figures, tables, and methods.