SDPRX

SDPRX integrates GWAS summary statistics across populations to improve cross-population polygenic risk score prediction accuracy for complex traits.

Key Features:

• Cross-Population Integration: Integrates GWAS summary statistics from multiple populations to inform joint analyses for polygenic risk score (PRS) construction.
• Adjustment for Linkage Disequilibrium (LD): Adjusts for differences in linkage disequilibrium (LD) patterns across populations when estimating variant effects.
• Joint Distribution Characterization: Characterizes the joint distribution of effect sizes of genetic variants across two populations, modeling null effects, population-specific effects, and shared effects with correlation.
• PRS Transferability Improvement: Enhances transferability and prediction accuracy of polygenic risk scores in non-European populations.
• Empirical Validation: Assesses performance via simulations and real-world datasets, reporting improved predictive performance compared to existing methods.

Scientific Applications:

• Cross-Population PRS Prediction: Construction and evaluation of polygenic risk scores for complex traits across diverse populations, including non-European cohorts.
• Genetic Risk Stratification: Identifying individuals at elevated genetic risk for disease to support research on disease etiology, personalized medicine, and population health strategies.

Methodology:

Statistical modeling that integrates GWAS summary statistics across populations, adjusts for population-specific LD, characterizes joint effect-size distributions across two populations (null, population-specific, shared with correlation), and evaluates performance via simulations and real-world datasets.