An Efficient Lasso Framework for Admixture-Aware Polygenic Scores.

ABSTRACT: Polygenic scores (PGS) have promising clinical applications for risk stratification, disease screening, and personalized medicine. However, most PGS are trained on predominantly European ancestry cohorts and have limited portability to external populations. While cross-population PGS methods have demonstrated greater generalizability than single-ancestry PGS, they fail to properly account for individuals with recent admixture between continental ancestry groups. GAUDI is a recently proposed PGS method which overcomes this gap by leveraging local ancestry to estimate ancestry-specific effects, penalizing but allowing ancestry-differential effects. However, the modified fused LASSO approach used by GAUDI is computationally expensive and does not readily accommodate more than two-way admixtur

SUBMITTER: Ockerman F 

PROVIDER: S-EPMC12407912 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature