To test whether FINEMAP is able to pick up this complex association pattern, we extracted a 2 megabase region centered on rs356220 with 363 directly genotyped SNPs from the original genotype data. Single-SNP testing using a logistic model implemented in SNPTEST was performed to compute z-scores. The dataset was then analyzed with FINEMAP using 100 iterations and prior parameter value of sλ2=0.052. Top panel of Figure 6 shows that the evidence that rs356220 and rs7687945 are causal is the largest among all SNPs. In addition, the causal configuration that simultaneously contains both rs356220 and rs7687945 has the highest posterior probability (0.132). The second most probable (0.113) causal configuration contains rs356220 and rs2301134. High correlation between rs7687945 and rs2301134 (r2=0.974) explains why these two SNPs are difficult to tell apart. We conclude that FINEMAP was able to identify the complex association pattern at the second SNP that only became identifiable after the first SNP was included in the model. As opposed to the standard conditional analysis, FINEMAP provides posterior probabilities for all SNPs in the region and is thus able to simultaneously identify many causal variants without a step-wise procedure.
