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Hybrid Bayes factors for genome-wide association studies when a robust test is used

By Gang Zheng, Ao Yuan and Neal Jeffries

Abstract

Bayes factor (BF) is often used to measure evidence against the null hypothesis in Bayesian hypothesis testing. In the analysis of genome-wide association (GWA) studies, extreme BF values support the associations detected based on significant p-values. Results from recent GWA studies are presented, which show that existing BFs may not be consistent withp-values when a robust test is used due to using different genetic models in the BF and p-value approaches and this may result in misleading conclusions. Two hybrid BFs, which combine the advantages of both the frequentist and Bayesian methods, are then proposed for the markers showing at least moderate associations (p-valueBayesian model averaging Bayes factors Genetic models Genome-wide scan and ranking Posterior weighted likelihood Profile likelihood

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