Scalable and Robust Regression Methods for Phenome-Wide Association Analysis on Large-Scale Biobank Data

被引：5

作者：

Bi, Wenjian ^{[1
,2
,3
]}

Lee, Seunggeun ^{[4
]}

机构：

[1] Peking Univ, Sch Basic Med Sci, Dept Med Genet, Beijing, Peoples R China

[2] Univ Michigan, Dept Biostat, Ann Arbor, MI 48109 USA

[3] Univ Michigan, Ctr Stat Genet, Ann Arbor, MI 48109 USA

[4] Seoul Natl Univ, Grad Sch Data Sci, Seoul, South Korea

来源：

FRONTIERS IN GENETICS | 2021年 / 12卷

基金：

新加坡国家研究基金会;

关键词：

phenome-wide association studies; electronic health records-EHR; saddlepoint approximation; biobank data analysis; unbalanced phenotypic distribution; genetic relatedness; mixed model approaches; GENE-ENVIRONMENT INTERACTION; MIXED-MODEL ANALYSIS; RARE VARIANTS; POPULATION-STRUCTURE; COMMON DISEASES; SEQUENCING DATA; TESTS; METAANALYSIS; SURVIVAL; POWER;

D O I：

10.3389/fgene.2021.682638

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

With the advances in genotyping technologies and electronic health records (EHRs), large biobanks have been great resources to identify novel genetic associations and gene-environment interactions on a genome-wide and even a phenome-wide scale. To date, several phenome-wide association studies (PheWAS) have been performed on biobank data, which provides comprehensive insights into many aspects of human genetics and biology. Although inspiring, PheWAS on large-scale biobank data encounters new challenges including computational burden, unbalanced phenotypic distribution, and genetic relationship. In this paper, we first discuss these new challenges and their potential impact on data analysis. Then, we summarize approaches that are scalable and robust in GWAS and PheWAS. This review can serve as a practical guide for geneticists, epidemiologists, and other medical researchers to identify genetic variations associated with health-related phenotypes in large-scale biobank data analysis. Meanwhile, it can also help statisticians to gain a comprehensive and up-to-date understanding of the current technical tool development.

引用

页数：12

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