Bayesian statistical methods for genetic association studies

被引：312

作者：

Stephens, Matthew ^{[1
,2
]}

Balding, David J. ^{[3
]}

机构：

[1] Univ Chicago, Dept Stat, Chicago, IL 60637 USA

[2] Univ Chicago, Dept Human Genet, Chicago, IL 60637 USA

[3] Univ London Imperial Coll Sci Technol & Med, Dept Epidemiol & Publ Hlth, London W2 1PG, England

来源：

NATURE REVIEWS GENETICS | 2009年 / 10卷 / 10期

基金：

美国国家卫生研究院;

关键词：

GENOME-WIDE ASSOCIATION; FALSE DISCOVERY; SELECTION; METAANALYSES;

D O I：

10.1038/nrg2615

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

Bayesian statistical methods have recently made great inroads into many areas of science, and this advance is now extending to the assessment of association between genetic variants and disease or other phenotypes. We review these methods, focusing on single-SNP tests in genome-wide association studies. We discuss the advantages of the Bayesian approach over classical (frequentist) approaches in this setting and provide a tutorial on basic analysis steps, including practical guidelines for appropriate prior specification. We demonstrate the use of Bayesian methods for fine mapping in candidate regions, discuss meta-analyses and provide guidance for refereeing manuscripts that contain Bayesian analyses.

引用

收藏

页码：681 / 690

页数：10

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