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Updated: Jun 1, 2026

A Quantitative Fitness Analysis Workflow
Published on: August 13, 2012
Behavior of QQ-plots and genomic control in studies of gene-environment interaction
Arend Voorman1, Thomas Lumley, Barbara McKnight
1Department of Biostatistics, University of Washington, Seattle, Washington, United States of America.
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 x 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 x E GWAS, and how this differs from main-effects analyses. We also explain how simple adjustments to standard regression-based methods used in G x E GWAS can alleviate this problem.
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