A short review on Genome-Wide Association Studies

被引：4

作者：

Cao, Xiaowen ^{[1
,3
]}

Xing, Li ^{[2
]}

He, Hua ^{[1
]}

Zhang, Xuekui ^{[3
]}

机构：

[1] Hebei Univ Techol, Dept Math, Tianjin, Peoples R China

[2] Univ Saskatchewan, Dept Math & Stat, Saskatoon, SK, Canada

[3] Univ Victoria, Dept Math & Stat, Victoria, BC, Canada

来源：

BIOINFORMATION | 2020年 / 16卷 / 05期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Genome-Wide Association Studies; Single Nucleotide Polymorphisms; Statistical power; Multiple Testing Adjustment; Linkage Disequilibrium; Supervised Learning; Unsupervised Learning; LINKAGE DISEQUILIBRIUM; MODEL; INFORMATION;

D O I：

10.6026/97320630016393

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Genome-wide association study (GWAS) is a popular approach to investigate relationship between genetic information and diseases. A large number of associations are tested in a single study, and the test results are corrected by multiple testing adjustment methods. It is observed that a substantial proportion of GWAS studies suffer considerable statistical power to assess reliability. Hence, we document available information on GWAS in this short review for glean insights.

引用

页码：393 / 395

页数：3

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