To identify causal variants that are likely to underlie cis-eQTLs, we applied two computational fine-mapping strategies25,26 (Supplementary Information 13 and Supplementary Figs 11, 18). First, we identified 90% credible sets (that is, the collection of variants with 90% probability of containing all causal variants) for each eGene in each tissue using CAVIAR25. Across all tissues, the mean credible set size was 29 variants (per tissue means ranged from 25 to 31). Second, we estimated the probability that each eVariant is a causal variant using CaVEMaN26. Across tissues, between 3.5% and 11.7% of top eVariants were predicted to be causal variants (causal probability P > 0.8). Consistent with variants with high causal probabilities being functional regulatory variants (as opposed to linkage disequilibrium proxies), 24.3% of eVariants with causal probabilities in the top tenth percentile (0.77 <P < 1) lay in open chromatin regions, while only 6.56% of eVariants in the lowest tenth percentile (0.0266 <P < 0.189) lay in such regions (Fig. 3d).
