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PolygenicRiskEngine

Pure Python polygenic risk score analysis pipeline.

Features

  • GWAS summary statistics simulation
  • LD clumping (r2<0.1, 500kb window)
  • C+T PRS computation
  • P-value threshold optimization (AUC)
  • Population stratification PCA
  • Risk percentile odds ratios

Usage

pip install numpy scipy pandas matplotlib
python polygenic_risk_engine.py

Results (1000 individuals, 5000 SNPs, 3 diseases)

  • T2D AUC=0.55 at p<5e-8 threshold
  • Top 10% vs bottom 10% OR=1.49
  • PC1 explains 0.3% variance

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Polygenic risk scores: C+T method, LD clumping, population stratification PCA

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