The extensive and diverse tissue sampling allowed us to develop a global view of how genetic effects vary between tissues of the human body by evaluating the sharing of eQTLs across tissues. We performed a meta-analysis across all 44 tissues for both cis- and trans-eQTLs to assess eQTL sharing between tissues. To do so, we applied Meta-Tissue15, a linear mixed model that allows for heterogeneity in effect sizes across tissues and controls for correlated expression measurements that result from collecting multiple tissues from the same donors. For each eQTL, we estimated the posterior probability that the effect is shared in each tissue (m value). For both cis- and trans-eQTLs, we observed patterns that reflected relationships between related tissues and concordance between cis and trans in estimates of tissue similarity (Fig. 2a, Supplementary Information 12 and Supplementary Fig. 17). The strongest broad pattern observed was the high correlation among brain tissues (median Spearman’s ρ of 0.584 (cis) and 0.241 (trans)) and among non-brain tissues (median Spearman’s ρ of 0.606 (cis) and 0.165 (trans)), with much lower correlation observed between these two
