Integrating predicted transcriptome from multiple tissues improves association detection
Panel a illustrates the S-MultiXcan method: the joint effect sizes are inferred from the marginal univariate effect sizes obtained from S-PrediXcan. Significance is quantified using the estimated covariance of the multivariate effect sizes. With the approximations described in Methods, the final χ2 statistics ends up being equivalent to the omnibus test. Panel b compares the number of associations significant via S-MultiXcan versus those significant via S-PrediXcan, for the same GWAS Studies. In most cases, S-MultiXcan detects a larger number of significant associations. The number of discoveries was thresholded at 200 for visualization purposes. Panel c displays QQ-Plots for the association p-values from S-MultiXcan and S-PrediXcan in Schizophrenia, using a model trained on brain’s cerebellum, and S-PrediXcan associations for all 44 GTEx tissues. Panel d shows the number of significant associations across all public GWAS traits for each method as a bar plot.