GRAMMAR-Lambda: An Extreme Simplification for Genome-wide Mixed Model Association Analysis

Abstract

AbstractA highly efficient genome-wide association method, GRAMMAR-Lambda is proposed to make simple genomic control for the test statistics deflated by GRAMMAR, producing statistical power as high as exact mixed model association method. Using the simulated and real phenotypes, we show that at a moderate or above genomic heritability, polygenic effects can be estimated using a small number of randomly selected markers, which extremely simplify genome-wide association analysis with an approximate computational complexity to naïve method in large-scale complex population. Upon a test at once, joint association analysis offers significant increase in statistical power over existing methods.