Variable selection method for quantitative trait analysis based on parallel genetic algorithm

Abstract

P>Selection of important genetic and environmental factors is of strong interest in quantitative trait analyses. In this study, we use parallel genetic algorithm (PGA) to identify genetic and environmental factors in genetic association studies of complex human diseases. Our method can take account of both multiple markers across the genome and environmental factors, and also can be used to do fine mapping based on the results of haplotype analysis to select the markers that are associated with the quantitative traits. Using both simulated and real examples, we show that PGA is able to choose the variables correctly and is also an easy-to-use variable selection tool.