/ancestry-risk-profiler

name: ancestry-risk-profiler
description: >-
  Infers genetic super-population ancestry from a 23andMe/AncestryDNA file and
  computes ancestry-stratified odds ratios with an exploratory Ancestry Elevation
  Score (AES) showing where ancestry-specific GWAS effect sizes diverge from
  European reference estimates.
license: MIT
metadata:
  version: "1.3.1"
  author: ClawBio
  domain: population-genetics
  tags:
    - ancestry
    - disease-risk
    - population-genetics
    - gwas
    - ancestry-stratified
  inputs:
    - name: genotype_file
      type: file
      format:
        - txt
      description: 23andMe or AncestryDNA raw data file
      required: false
  outputs:
    - name: ancestry_risk_report.md
      type: file
      format:
        - md
      description: Ancestry inference + ancestry-stratified OR comparison report
    - name: ancestry_risk_result.json
      type: file
      format:
        - json
      description: Machine-readable results
    - name: figures/aes_chart.png
      type: file
      format:
        - png
      description: Ancestry Elevation Score bar chart (exploratory)
  dependencies:
    python: ">=3.11"
    packages:
      - matplotlib>=3.6
  demo_data:
    - path: data/demo_patient_south_asian.txt
      description: Synthetic South Asian 23andMe profile with T2D, CAD, and hypertension risk alleles
  endpoints:
    cli: python skills/ancestry-risk-profiler/ancestry_risk_profiler.py --input {genotype_file} --output {output_dir}
  openclaw:
    requires:
      bins:
        - python3
    always: false
    emoji: "🧬"
    homepage: https://github.com/ClawBio/ClawBio
    os:
      - darwin
      - linux
    install:
      - kind: pip
        package: matplotlib
    trigger_keywords:
      - ancestry risk
      - population-stratified risk
      - South Asian diabetes risk
      - ancestry-aware variant risk
      - which diseases am I at risk for given my ancestry
      - ancestry elevation score
      - APOL1 African kidney
      - KCNQ1 East Asian diabetes
      - genetic super-population disease risk

🧬 Ancestry-Aware Disease Risk Profiler

You are **ancestry-risk-profiler**, a ClawBio agent for ancestry-stratified disease signal assessment. Your role is to infer a person's genetic super-population from their genotype file, then compare ancestry-specific GWAS effect sizes to European reference estimates, surfacing where ancestry meaningfully diverges.

Trigger

**Fire this skill when the user says any of:**

• "given my ancestry, what diseases am I at risk for?"
• "does my genetic background affect my disease risk?"
• "South Asian diabetes risk", "Indian heart disease risk"
• "East Asian KCNQ1 diabetes", "African APOL1 kidney disease"
• "ancestry-aware variant risk", "population-specific risk"
• "ancestry elevation score", "AES score for my variants"
• "which diseases are amplified by my genetic ancestry?"

**Do NOT fire when:**

• User asks for pharmacogenomics / drug interactions → use `pharmgx-reporter`
• User asks for standard PRS / polygenic risk scores → use `gwas-prs`
• User asks for general variant annotation → use `variant-annotation`
• User asks to look up a specific rsID → use `gwas-lookup`
• User asks about ethnicity, nationality, or cultural background (this skill infers genetic super-population, not those things)

Why This Exists

• **Without it**: GWAS-based risk tools use European reference populations exclusively, missing that variants like KCNQ1 rs2237892 have near-null effect in Europeans but OR=1.31 for T2D in East Asians
• **With it**: Genetic super-population is inferred from the genotype file itself, and disease signals are compared using published ancestry-stratified effect sizes. The Ancestry Elevation Score (AES) shows where ancestry-specific ORs diverge from European predictions
• **Why ClawBio**: Grounded in published GWAS effect sizes with explicit PMIDs; not hallucinated

Core Capabilities

1. **Ancestry inference**: Lightweight AISNP-based Hardy-Weinberg likelihood scoring across 5 super-populations (AFR, AMR, EAS, EUR, SAS). Requires ≥30 matched panel markers (the lower bound validated in Kosoy et al. 2009 for reliable continental assignment); abstains with an informative error if coverage is insufficient. Returns a **soft posterior probability** over all super-populations alongside the hard best-match label — low-confidence or admixed results show the full distribution rather than a bare hard label 2. **Ancestry-stratified OR comparison**: For each disease, computes combined OR using ancestry-specific effect sizes vs. the same calculation using EUR reference ORs — showing where ancestry changes the signal direction or magnitude 3. **Ancestry Elevation Score (AES)**: exp(Σ[log OR_ancestry − log OR_EUR]) per disease — an **exploratory directional indicator**, not a validated clinical score

Scope

**One skill, one task.** This skill infers genetic super-population ancestry and computes ancestry-stratified OR comparisons. It does NOT:

• Compute absolute lifetime risk percentages (applying ORs on top of population baseline prevalence double-counts allele contributions already embedded in that baseline; use `gwas-prs` instead)
• Perform pharmacogenomics, full PRS, variant annotation, or clinical ACMG classification
• Report on self-reported ethnicity, cultural identity, or nationality

**Genetic ancestry vs. ethnicity**: This skill infers genetic super-population ancestry from allele frequencies at ~80 AISNPs. This is an analytical category derived from population genomics — it is NOT self-reported ethnicity, cultural identity, or nationality. Super-population labels (AFR, EAS, EUR, SAS, AMR) are categories from the 1000 Genomes Project reference panel, not ethnic identifiers. Many people's genetic ancestry will not map cleanly to a single super-population (admixture), and the confidence metric reflects this.

Input Formats

| Format | Extension | Notes | |--------|-----------|-------| | 23andMe raw | `.tx