Detecting gene-gene interactions that underlie human diseases

被引：982

作者：

Cordell, Heather J. ^{[1
]}

机构：

[1] Univ Newcastle, Inst Human Genet, Int Ctr Life, Newcastle Upon Tyne NE1 3BZ, Tyne & Wear, England

来源：

NATURE REVIEWS GENETICS | 2009年 / 10卷 / 06期

基金：

英国惠康基金;

关键词：

GENOME-WIDE ASSOCIATION; DIMENSIONALITY REDUCTION METHOD; SAMPLE-SIZE REQUIREMENTS; QUANTITATIVE TRAIT LOCI; HIGH-ORDER INTERACTIONS; ENVIRONMENT INTERACTIONS; COMBINATORIAL APPROACH; EPISTATIC INTERACTIONS; STATISTICAL EPISTASIS; RHEUMATOID-ARTHRITIS;

D O I：

10.1038/nrg2579

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

Following the identification of several disease-associated polymorphisms by genome-wide association (GWA) analysis, interest is now focusing on the detection of effects that, owing to their interaction with other genetic or environmental factors, might not be identified by using standard single-locus tests. In addition to increasing the power to detect associations, it is hoped that detecting interactions between loci will allow us to elucidate the biological and biochemical pathways that underpin disease. Here I provide a critical survey of the methods and related software packages currently used to detect the interactions between genetic loci that contribute to human genetic disease. I also discuss the difficulties in determining the biological relevance of statistical interactions.

引用

页码：392 / 404

页数：13

共 114 条

[41] Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions [J].