Pathway-based approaches for analysis of genomewide association studies

被引：690

作者：

Wang, Kai ^{[1
]}

Li, Mingyao

Bucan, Maja

机构：

[1] Univ Penn, Dept Genet, Philadelphia, PA 19104 USA

[2] Univ Penn, Dept Biostat & Epidemiol, Philadelphia, PA 19104 USA

来源：

AMERICAN JOURNAL OF HUMAN GENETICS | 2007年 / 81卷 / 06期

关键词：

D O I：

10.1086/522374

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

Published genomewide association (GWA) studies typically analyze and report single-nucleotide polymorphisms (SNPs) and their neighboring genes with the strongest evidence of association (the "most-significant SNPs/genes" approach), while paying little attention to the rest. Borrowing ideas from microarray data analysis, we demonstrate that pathway-based approaches, which jointly consider multiple contributing factors in the same pathway, might complement the most-significant SNPs/genes approach and provide additional insights into interpretation of GWA data on complex diseases.

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页码：1278 / 1283

页数：6

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