Comparison of Statistical Methods for Estimating Genetic Admixture in a Lung Cancer Study of African Americans and Latinos

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Abstract
A variety of methods are available for estimating genetic admixture proportions in populations; however, few investigators have conducted detailed comparisons using empirical data. The authors characterized admixture proportions among self-identified African Americans (n = 535) and Latinos (n = 412) living in the San Francisco Bay Area who participated in a lung cancer case-control study (1998–2003). Individual estimates of genetic ancestry based on 184 informative markers were obtained from a Bayesian approach and 2 maximum likelihood approaches and were compared using descriptive statistics, Pearson correlation coefficients, and Bland-Altman plots. Case-control differences in individual admixture proportions were assessed using 2-sample t tests and logistic regression analysis. Results indicated that Bayesian and frequentist approaches to estimating admixture provide similar estimates and inferences. No difference was observed in admixture proportions between African-American cases and controls, but Latino cases and controls significantly differed according to Amerindian and European genetic ancestry. Differences in admixture proportions between Latino cases and controls were not unexpected, since cases were more likely to have been born in the United States. Genetic admixture proportions provide a quantitative measure of ancestry differences among Latinos that can be used in analyses of genetic risk factors.

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