Testing these large number of mirSNPs using GWAS requires statistical correction for multiple testing, such as the Bonferroni correction. The low minor allele frequency of many causal variants, and routine multiple comparisons corrections make it very difficult, or impossible, to statistically identify functionally relevant variants in genome-wide studies. Consequently, in GWAS, impractically large numbers of subjects from diverse populations would be required to identify rare functional variants that are statistically significant. Lowering the statistical threshold or not correcting for multiple comparisons increases the sensitivity to detect rare variant associations, but results in the detection of many false positives signals. Despite some technical challenges, high-throughput in vitro approaches have been implemented that are specific to variants in certain non-coding regions, such as splice-junctions (Soemedi et al., 2014) and promoters (Kwasnieski et al., 2012; Melnikov et al., 2012). However, we are not aware of any high-throughput assays available to functionally test variants in miRNA binding sites (Ipe et al., 2017).
