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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.