We compared our approach to a several of existing methods that can be used for fine-mapping[5], [10], [12], [13], [14]. To compute Maller et al. [5] posterior probabilities, we first calculated Bayes factors with the R package, BayesFactor, using the default settings. We converted the resultant Bayes factors into posterior probabilities of association using the following formula: . We show in Figure S8 and Supplementary Note S1 that posterior probabilities approximated directly from the Z-scores give virtually indistinguishable results. We downloaded fgwas [10] version 0.3.4 from GitHub and ran the software using the -fine flag. Due to the fact that we fit linear models to obtain Wald statistics for each SNP, we were able to provide standard errors for the estimates of the prior variance. We segmented our input based on the individual loci as instructed in user manual, but provided a single file that contained all the fine-mapping SNPs so that fgwas could compute enrichment. The Guan and Stephens [14] method is implemented in the software piMass which we ran using the flags and MCMC parameters given in the
