连锁不平衡
人口
遗传关联
联动装置(软件)
全基因组关联研究
可转让性
统计
生物
相关性
计算机科学
机器学习
进化生物学
遗传学
基因型
单倍型
人口学
数学
罗伊特
基因
社会学
单核苷酸多态性
几何学
作者
Geyu Zhou,Tianqi Chen,Hongyu Zhao
标识
DOI:10.1016/j.ajhg.2022.11.007
摘要
Polygenic risk score (PRS) has demonstrated its great utility in biomedical research through identifying high-risk individuals for different diseases from their genotypes. However, the broader application of PRS to the general population is hindered by the limited transferability of PRS developed in Europeans to non-European populations. To improve PRS prediction accuracy in non-European populations, we develop a statistical method called SDPRX that can effectively integrate genome wide association study summary statistics from different populations. SDPRX automatically adjusts for linkage disequilibrium differences between populations and characterizes the joint distribution of the effect sizes of a variant in two populations to be both null, population specific, or shared with correlation. Through simulations and applications to real traits, we show that SDPRX improves the prediction performance over existing methods in non-European populations.
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