Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/22043
Title: GCTA: A Tool for Genome-wide Complex Trait Analysis
Contributor(s): Yang, Jian (author); Lee, Sang Hong  (author); Goddard, Michael E. (author); Visscher, Peter M. (author)
Publication Date: 2011
Open Access: Yes
DOI: 10.1016/j.ajhg.2010.11.011Open Access Link
Handle Link: https://hdl.handle.net/1959.11/22043
Open Access Link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3014363/Open Access Link
Abstract: 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.
Publication Type: Journal Article
Source of Publication: The American Journal of Human Genetics, 88(1), p. 76-82
Publisher: Cell Press
Place of Publication: United States of America
ISSN: 1537-6605
0002-9297
Field of Research (FOR): 060405 Gene Expression (incl. Microarray and other genome-wide approaches)
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
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