Association Studies with Imputed SNPs Using Expectation-Maximization-Likelihood-Ratio Test

• Activity Number: 456
• Type: Contributed
• Date/Time: Wednesday, August 6, 2014 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): Kuan-Chieh Huang*+ and Yun Li
• Companies: University of North Carolina at Chapel Hill and University of North Carolina at Chapel Hill
• Keywords: association ; genotype imputation ; EM algorithm ; likelihood ratio test

Abstract

We propose new methods that attempt to more elegantly incorporate uncertainty when analyzing imputed genotypes with covariate adjustment conveniently accommodated. We consider two scenarios: 1) when posterior probabilities of all potential genotypes are estimated or 2) when only one-dimensional summary statistic imputed dosages are available. We have developed an expectation-maximization (EM) likelihood-ratio test (LRT) for association based on posterior probabilities (scenario 1). When only imputed dosages are available (scenario 2), we first sample the probabilities of all possible genotypes from the dosages and then apply the EM-LRT on the sampled probabilities. Extensive simulations have shown that type I error rates of the EM-LRT methods under both scenarios are protected. Furthermore, EM-LRT-Prob offers enhanced statistical power across the whole spectrum of imputation quality and EM-LRT-Dose retains similar level of statistical power as EM-LRT-Prob and, more importantly, show advantages over the standard dosage method, especially for markers with relatively low imputation quality.