Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics (original) (raw)
Figure 5
Summary of proportional and Bayesian colocalisation analysis of simulated data.
Each plot shows a different scenario, the total number of causal variants in a region is indicated by number of circles in the plot titles with causal variants affecting both traits, the eQTL trait only, or the biomarker trait only, indicated by full circles, top-shaded circles and bottom-shaded circles respectively. In the top row the causal variant is typed or imputed, whereas only tag variants are typed/imputed in the bottom row. For proportional testing (under the BMA approach), we show the proportion of simulations with posterior predictive p-value <0.05 (black horizontal line) while for our Bayesian analysis we plot the proportion of simulations with the posterior probability (PP3 or PP4) of the indicated hypothesis >0.9. Error bars show 95% confidence intervals (estimated based on an average of 1,000 simulations per scenario). In all cases, for the eQTL sample size is 1,000; genetic variants explain a total of 10% of eQTL variance; for the biomarker trait, the sample size is 10,000.