Extended Data Figure 4. Identification of cis-acting eQTLs using allele-specific expression at chromosome-wide distances.

a, A logistic regression based model was developed to predict the probability of phasing error as a function of distance and variant minor allele frequencies. When applied to chromosome 2 of 1000 Genomes sample NA12878, this model had a receiver operating characteristic (ROC) area under the curve (AUC) of 0.87 using population phasing compared to transmission phasing. b, ROC when applying the beta-binomial mixture model to detect cis-acting regulation to the GTEx v6p subcutaneous adipose cis-eQTLs, with an AUC of 0.88. As the null, eGenes were shuffled with respect to eVariants. c, Power analysis using all nominally significant (P <1.0 ×10⁻⁵) linkage disequilibrium pruned associations within 100 kb of the TSS illustrating the number of eQTLs with nominally significant (P ≤ 0.01) evidence of cis-regulation as a function of phasing error and eQTL effect size. Expression QTL effect size was calculated using a companion method²⁸, and uniform phasing error between 0 and 100% was introduced in silico. d, Proportion of nominally significant (P <1.0 ×10⁻⁵) linkage disequilibrium-pruned intrachromosomal eQTLs with nominally significant (P ≤ 0.01) ASE supported evidence of cis regulation in bins of increasing TSS distance. Observed indicates what is seen in the data, while Max Error indicates what would be expected in the worst-case scenario of phasing error (50%). e, Example of significant ASE supported cis-regulation at a distance of 52.7 Mb between eVariant rs17494053 and eGene ENSG00000108509 in whole blood. Each point represents allelic imbalance in a single eVariant homozygote (circle) or heterozygote (triangle).