not bias mean gene expression in any specific tissue. We used the Jackknife approach that removes one gene at a time to estimate the sampling variance of \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 (Methods) assuming the estimated top cis-eQTL effects for different genes are independent. This assumption was approximately met given the small LD correlations among the 4257 cis-eQTLs and the subtle difference between the mean Jackknife sampling variance and the observed sampling variance in simulation (Supplementary Fig. 4).
