Behavior of QQ-plots and Genomic Control in studies of gene-environment interaction

Abstract

Genome-wide association studies of gene-environment interaction (GxE GWAS) are becoming popular. As with main effects GWAS, quantile-quantile plots (QQ-plots) and Genomic Control are being used to assess and correct for population substructure. However, in G × E work these approaches can be seriously misleading, as we illustrate; QQ-plots may give strong indications of substructure when absolutely none is present. Using simulation and theory, we show how and why spurious QQ-plot inflation occurs in G × E GWAS, and how this differs from main-effects analyses. We also explain how simple adjustments to standard regression-based methods used in G × E GWAS can alleviate this problem. © 2011 Voorman et al.