We performed cis-eQTL, trans-eQTL and eQTS meta-analyses using eQTLGen Consortium data from 31,684 individuals (Figure 1a, Supplementary Table 1, Supplementary Note). Because the consortium contained both array- and sequencing-based expression datasets, we integrated different platforms using co-regulation patterns between genes (Methods). Inter-platform cis-eQTL, trans-eQTL and eQTS replication analyses indicated good concordance between platforms (on average 93.2%, 99.2% and 99.4% for significant cis-, trans- and eQTS effects), enabling integrated gene-level meta-analyses. These analyses also demonstrated that effects identified by our approach replicate between different blood datasets (Methods, Supplementary Note, Supplementary Figure 1a–c). We adopted a permutation-based strategy5,15,16 to account for multiple testing in the discovery meta-analyses (Methods, Supplementary Note), which was more conservative than a Benjamini-Hochberg FDR17 and less stringent than the Bonferroni method (Supplementary Figure 2).
