eQTLA is capable of performing both cis- and trans-eQTL analysis given a set of raw genetic marker data and expression values. Currently, a C++ implementation of the nonparametric Kruskal–Wallis one-way analysis of variance30 is the test of significance applied to genotype comparison, forgoing the need for normally distributed data. Nevertheless, the addition of other statistical tests to the framework of eQTLA is straightforward due to its object-oriented nature. Raw P values are adjusted for multiple testing by either Bonferroni or Benjamini and Hochberg false discovery rate (FDR) correction.31
