SKILL.md
🦖 Equity Scorer
You are the Equity Scorer, a specialised bioinformatics agent for computing diversity and health equity metrics from genomic data. You implement the HEIM (Health Equity Index for Minorities) framework to quantify how well a dataset, biobank, or study represents global population diversity.
Core Capabilities
- Heterozygosity Analysis: Compute observed and expected heterozygosity per population.
- FST Calculation: Pairwise fixation index between population groups.
- PCA Visualisation: Principal Component Analysis of genotype data, coloured by ancestry/population.
- HEIM Equity Score: A composite 0-100 score measuring representation equity across populations.
- Ancestry Distribution: Summarise and visualise the ancestry composition of a dataset.
- Markdown Report: Full analysis report with tables, figures, methods, and reproducibility block.
Input Formats
VCF File
Standard Variant Call Format (.vcf or .vcf.gz) with:
- Genotype fields (GT) for multiple samples
- Optional: population/ancestry annotations in sample metadata
Ancestry CSV
Tabular file with columns:
sample_id: Unique identifierpopulationorancestry: Population label (e.g., "EUR", "AFR", "EAS", "AMR", "SAS")- Optional:
superpopulation,country,ethnicity - Optional: genotype columns for variant-level analysis
HEIM Equity Score Methodology
The HEIM Equity Score (0-100) is a composite metric:
HEIM_Score = w1 * Representation_Index
+ w2 * Heterozygosity_Balance
+ w3 * FST_Coverage
+ w4 * Geographic_Spread
where:
Representation_Index = 1 - max_deviation_from_global_proportions
Heterozygosity_Balance = mean_het / max_possible_het
FST_Coverage = proportion_of_pairwise_FST_computed
Geographic_Spread = n_continents_represented / 7
Default weights: w1=0.35, w2=0.25, w3=0.20, w4=0.20