Compute HEIM diversity and equity metrics from VCF or ancestry CSV files.
npx skills add https://github.com/ClawBio/ClawBio --skill equity-scorer
Please help me install this Agent Skill. Skill: equity-scorer Source: https://github.com/ClawBio/ClawBio/tree/main/skills/equity-scorer Command: npx skills add https://github.com/ClawBio/ClawBio --skill equity-scorer
Measure how well a genomic dataset represents global population diversity and detect underrepresentation that can bias downstream analyses, by turning genotype or ancestry files into interpretable equity metrics and visualisations.
Run the equity-scorer on a VCF or ancestry CSV to compute heterozygosity, pairwise FST, PCA plots, and a HEIM Equity Score with a reproducible markdown report.
High-intent search queries and answers about installing and using this skill.
Quantify population representation in a VCF file by computing observed heterozygosity, pairwise FST, PCA plots, and a composite 0-100 HEIM equity score. The process outputs a reproducible directory with markdown reports, figures, and CSV tables.
A HEIM equity score is a 0-100 composite metric that detects ancestry underrepresentation in biobanks by quantifying heterozygosity, population differentiation, and ancestry distributions. It flags biases that can skew downstream genomic analyses.
Yes, you can use ancestry CSV files instead of multi-sample VCFs for pairwise FST and heterozygosity analysis. The computation accepts both formats to evaluate cohort ancestry composition and generate PCA visualizations.
The best way to compare cohort recruitment strategies using population genetics metrics is to calculate pairwise FST, heterozygosity comparisons, and ancestry distributions. This produces publication-ready visuals and a HEIM gauge for equity assessment.
Equity scoring with Python does not require external servers for processing multi-sample VCF datasets. The computation operates locally using standard scientific libraries like numpy, pandas, scikit-learn, and matplotlib.
You should not use PCA and FST metrics for QC cohort ancestry composition when your input VCF or ancestry CSV files lack clear population labels, as the equity score calculation requires defined groups to compute heterozygosity and between-population structure.
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MubasherMohammedCompute HEIM diversity and equity metrics from VCF or ancestry data.
