To quantify the similarity of genetic effects at the top-associated cis-eQTLs (or cis-mQTLs) between two tissues, we used a summary-data-based approach to estimate the correlation of cis-effects between two tissues (rb) correcting for errors in the estimated cis-eQTL (or cis-mQTL) effects and sample overlap (Supplementary Fig. 1 and Methods). We showed by simulation (Supplementary Note 1) that rb is a good estimator of correlation of the true values of cis-genetic effects (Supplementary Fig. 2). Note that the rb method is distinct from the Spearman or Pearson correlation approach13 because the latter does not account for errors in the estimated eQTL effects and thereby leads to an underestimation of the correlation of true eQTL effects. We applied our method to estimate \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hat r_b$$\end{document}r^b at the top cis-eQTLs between different brain regions and between brain and blood in one data set, and between brain and blood in two data sets using summary-level data from GTEx v6 (whole blood and 10 brain regions)11, the CommonMind Consortium (CMC; dorsolateral prefrontal cortex)18, the Religious Orders Study
