The authors argue that population structure per se is not a problem in genome-wide association studies — the true sources are the environment and the genetic background, and the latter is greatly underappreciated. They conclude that mixed models effectively address this issue.
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We thank E. Buckler, D. Balding, P. Donnelly, A. Hancock, I. Hellmann, M. Horton, A. Korte, Q. Long, D. Meng, N. Patterson, A. Platt, A. Price, V. Segura, O. Stegle and Q. Zhang for discussions and/or comments on the manuscript. We are especially grateful to A. Price for sharing the observation that mixed models can explain a substantial fraction of the phenotypic covariance in randomly generated individuals. Remaining errors or omissions are our responsibility. This work was supported by US National Institutes of Health grant HG002790, European Research Council grant AdG-268962 and the Gregor Mendel Institute. We apologize to authors whose work could not be cited owing to space constraints.
The authors declare no competing financial interests.
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Vilhjálmsson, B., Nordborg, M. The nature of confounding in genome-wide association studies. Nat Rev Genet 14, 1–2 (2013). https://doi.org/10.1038/nrg3382
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