To pick a threshold for rejection of HWE using Bayes factors we need to specify the PO of H0, and the ratio of costs of type II to type I errors. In this context we would expect π1 = 1 – π0 to be very close to 0 (though not as close as the prior on a SNP being associated with disease), while we would not want to unnecessarily exclude a SNP from an association analysis, which suggests R≪1 (if in the association stage a signal is found, then clearly one would closely examine the control data from such a SNP). We choose π0 = 0.999 and R = 1/1000, which leads to a Bayes factor threshold of 10−7, so that the data have to be 107 times more likely under the alternative than under the null before HWE is rejected. This leads to 112 rejections under the conjugate prior Bayes factor and 100 under the triangular prior Bayes factor (we do not plot the latter as they are in close agreement with those under the conjugate prior).
