title: 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 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.
authors: Department of Biostatistics, University of Washington, Seattle, Washington, United States of America.
authors: Arend
authors: A
authors: Voorman
authors: Thomas
authors: T
authors: Lumley
authors: Barbara
authors: B
authors: McKnight
authors: Kenneth
authors: K
authors: Rice
references: Nat Rev Genet. 2005 Apr;6(4):287-98
references: 15803198
references: Nat Genet. 2009 Nov;41(11):1191-8
references: 19862010
references: PLoS One. 2009 Jul 09;4(7):e6138
references: 19587794
references: Nat Rev Genet. 2010 Apr;11(4):259-72
references: 20212493
references: Biometrics. 1999 Dec;55(4):997-1004
references: 11315092
references: Nat Genet. 2006 Aug;38(8):904-9
references: 16862161
references: PLoS One. 2008;3(10):e3392
references: 18852890
references: JAMA. 2008 Mar 19;299(11):1335-44
references: 18349094