Despite these advances, several challenges still remain in the field of genome-wide eQTL research. The large number of gene expression traits and genomic loci requires enormous calculations, raising issues of computer efficiency and statistical power. Another challenge is the varying genetic backgrounds in study populations, which may be one of the causes of the poor reproducibility observed across studies. Furthermore, confounding variables, such as the time of day at which sampling was performed, may also affect gene expression patterns in peripheral blood [13]. In addition, microarray probes may contain one or more SNPs in the target sequence. These probes may cause hybridization differences due to sequence polymorphisms present in the mRNA region, resulting in the occurrence of false positive results [14]. Other probes may undergo cross-hybridization, also resulting in false positive results for trans-eQTLs. The large number of probes and SNPs cause difficulties in accounting for these confounding and influencing variables. A limited number of studies have overcome these methodological issues; therefore, further accumulation of data is required. Specifically, genome-wide eQTL data for Asian population is scarce [15].
