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Chunk #68 — Online Methods — scRNA-seq analyses — Correlation of trans-eQTL effects

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Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression.
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In order to include independent effects in the analysis, for each trans-eQTL gene, we included only the strongest significant discovery effect in each 2 Mb window. Statistics of rb and SE(rb) were calculated as detailed in Qi et al. 201824 assuming no sample overlap between discovery and replication datasets. Because we were only seeking to correlate the effects of identified trans-eQTLs, we did not use any reference discovery dataset for selecting trans-eQTLs to estimate rb, and hence did not consider potential ascertainment bias, although such bias is likely to be small. To calculate a P-value, the Z-score was first calculated by dividing rb by SE(rb) and then squared to calculate the χ2 statistic. The P-value was then derived from the χ2 distribution with one degree of freedom.