Figure 5: Colocalisation analysis of Graves’ and Hashimoto’s diseases. Regions are labelled by chro- mosome and likely candidate gene(s) and arranged so that the top seven regions showed marginally significant association with both GD and HT ( p < 0 . 05) and the bottom six with just GD in the published single SNP analysis [Cooper et al., 2012]. The left panel shows the estimate of the co- efficient of proportionality, η , for the estimate of the ratio of effect sizes in HT compared to GD, and its 95% credible interval, calculated using either the PCs approach (PC), or BMA averaging over two SNP models (BMA.2) or three SNP models (BMA.3). The middle panel shows the the evidence against colocalisation using either the − log$_{10}$( p ) value (PCs) or the posterior predictive − log$_{10}$( p ) (BMA). The right panel summarizes the evidence for association of the region with each disease using − log$_{10}$( p ) values for the association analysis of Graves’ and Hashimoto’s using the selected principal components for the PCs approach. The − log$_{10}$ scale has been truncated at 10 so that more extreme p values are displayed at − log$_{10}$( p ) = 10. For the PC approach, testing was based on the smallest subset of components that captured 90% of the genetic variance. 30 14q31.1/TSHR 12q12/PRICKLE1 1q23.1/FCRL3 1p36.32/TNFRSF1 16p11.2/ITGAM 6q27/CCR6 2q33.2/CTLA4/ICOS 10p15.1/IL2RA 11q21/−− 1p13.2/PTPN22 6q15/BACH2 2p25.1/TRIB2 3q27.3/3q28/LPP 0.0 2.5 5.0 7.5 eta Chromosome region Coefficient of proportionality 0 2 4 −log10 P values Colocalisation test 0 2 4 6 8 10 −log10 P values Disease association Colocalisation, BMA.2 Colocalisation, BMA.3 Colocalisation, PC Disease, Graves Disease, Hashimoto