GCTA: A Tool for Genome-wide Complex Trait Analysis

被引：5339

作者：

Yang, Jian ^{[1
]}

Lee, S. Hong ^{[1
]}

Goddard, Michael E. ^{[2
,3
]}

Visscher, Peter M. ^{[1
]}

机构：

[1] Queensland Inst Med Res, Queensland Stat Genet Lab, Brisbane, Qld 4006, Australia

[2] Univ Melbourne, Dept Food & Agr Syst, Parkville, Vic 3010, Australia

[3] Dept Primary Ind, Biosci Res Div, Bundoora, Vic 3086, Australia

来源：

AMERICAN JOURNAL OF HUMAN GENETICS | 2011年 / 88卷 / 01期

基金：

澳大利亚研究理事会; 英国医学研究理事会;

关键词：

MISSING HERITABILITY; STRATIFICATION; ASSOCIATION; LOCI; PREDICTIONS; INFORMATION; SELECTION; DISEASES;

D O I：

10.1016/j.ajhg.2010.11.011

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

For most human complex diseases and traits, SNPs identified by genome-wide association studies (GWAS) explain only a small fraction of the heritability. Here we report a user-friendly software tool called genome-wide complex trait analysis (GCTA), which was developed based on a method we recently developed to address the "missing heritability" problem. GCTA estimates the variance explained by all the SNPs on a chromosome or on the whole genome for a complex trait rather than testing the association of any particular SNP to the trait. We introduce GCTA's five main functions: data management, estimation of the genetic relationships from SNPs, mixed linear model analysis of variance explained by the SNPs, estimation of the linkage disequilibrium structure, and GWAS simulation. We focus on the function of estimating the variance explained by all the SNPs on the X chromosome and testing-the hypotheses of dosage compensation. The GCTA software is a versatile tool to estimate and partition complex trait variation with large GWAS data sets.

引用

页码：76 / 82

页数：7

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