Population-based case-control association is a promising approach for unravelling the genetic basis of complex diseases. One potential problem of this approach is the presence of population structure in the samples. Using the Collaborative Study on the Genetics of Alcoholism (COGA) single-nucleotide polymorphism (SNP) datasets, we addressed three questions: How can the degree of population structure be quantified, and how does the population structure affect association studies? How accurate and efficient is the genomic control method in correcting for population structure? The amount of population structure in the COGA SNP data was found to inflate the p-value in association tests. Genomic control was found to be effective only when the appropriate number of markers was used in the control group in order to correctly calibrate the test. The approach presented in this paper could be used to select the appropriate number of markers for use in the genomic control method of correcting population structure.
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