Population structure, differential bias and genomic control in a large-scale, case-control association study |
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| Authors: | Clayton David G Walker Neil M Smyth Deborah J Pask Rebecca Cooper Jason D Maier Lisa M Smink Luc J Lam Alex C Ovington Nigel R Stevens Helen E Nutland Sarah Howson Joanna M M Faham Malek Moorhead Martin Jones Hywel B Falkowski Matthew Hardenbol Paul Willis Thomas D Todd John A |
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| Institution: | Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, University of Cambridge, Cambridge Institute for Medical Research, Wellcome Trust/MRC Building, Cambridge, CB2 2XY, UK. |
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| Abstract: | The main problems in drawing causal inferences from epidemiological case-control studies are confounding by unmeasured extraneous factors, selection bias and differential misclassification of exposure. In genetics the first of these, in the form of population structure, has dominated recent debate. Population structure explained part of the significant +11.2% inflation of test statistics we observed in an analysis of 6,322 nonsynonymous SNPs in 816 cases of type 1 diabetes and 877 population-based controls from Great Britain. The remainder of the inflation resulted from differential bias in genotype scoring between case and control DNA samples, which originated from two laboratories, causing false-positive associations. To avoid excluding SNPs and losing valuable information, we extended the genomic control method by applying a variable downweighting to each SNP. |
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