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 absolut...

There are several errors in mathematical expressions in theIntroduction under the subheading GWAS Plus: GCTA. In the final sentence of the second paragraph, the expression for the distribution of u is incorrect. The subscript n should be an m and the subscript epsilon should be a u. The correct distribution is: u∼Nmð0; IσuÞ. In the second sentence of the sixth paragraph, the expression for the ...

Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Jaboticabal, SP 14884-900, Brazil The University of Queensland, Queensland Alliance for Agriculture and Food innovation, Centre for Animal Science, Brisbane, Qld 4062, Australia CSIRO Food Futures Flagship and Animal, Health and Food Sciences, 306 Carmody Road, St Lucia, QLD 4067, Australia Faculdade de Medicina Vete...

Nada A. Al-Tassan, Nicola Whiffin, Fay J. Hosking, Claire Palles, Susan M. Farrington, Sara E. Dobbins, Rebecca Harris, Maggie Gorman, Albert Tenesa, Brian F. Meyer, Salma M. Wakil, Ben Kinnersley, Harry Campbell, Lynn Martin, Christopher G. Smith, Shelley Idziaszczyk, Ella Barclay, Timothy S. Maughan, Richard Kaplan, Rachel Kerr, David Kerr, Daniel D. Buchanan, Aung Ko Win, John Hopper, Mark J...

We introduce a method for learning pairwise interactions in a linear regression or logistic regression model in a manner that satisfies strong hierarchy: whenever an interaction is estimated to be nonzero, both its associated main effects are also included in the model. We motivate our approach by modeling pairwise interactions for categorical variables with arbitrary numbers of levels, and the...

Local adaptation is critical for species persistence in the face of rapid environmental change, but its genetic basis is not well understood. Growing the model plant Arabidopsis thaliana in field experiments in four sites across the species' native range, we identified candidate loci for local adaptation from a genome-wide association study of lifetime fitness in geographically diverse accessio...

There is an emerging appreciation that genome-wide association studies (GWAS) have failed to live up to expectations and deliver major advances to date. A "surge" strategy, of pooling resources and increasing number of subjects tested, is underway. We argue that, while useful, it will not be enough by itself. Complementary approaches are needed to mine these large datasets. We describe a series...

Genomewide association studies (GWAs) initially investigate hundreds of thousands of single-nucleotide polymorphisms (SNPs), and the most promising SNPs are further evaluated with additional subjects, for replication or a joint analysis. Deciding which SNPs merit follow-up is one of the most crucial aspects of these studies. We present here an approach for selecting the most-promising SNPs that...

Many public and private genome-wide association studies that we have analyzed include flaws in design, with avoidable confounding appearing as a norm rather than the exception. Rather than recognizing flawed research design and addressing that, a category of quality-control statistical methods has arisen to treat only the symptoms. Reflecting more deeply, we examine elements of current genomic ...

The stratification score for a case-control study is the probability of disease modeled as a function of potential confounders. The authors show that the stratification score is a retrospective balancing score and thus plays a similar role in case-control studies as the propensity score plays in prospective studies. The authors further show how standardization using the stratification score can...