There are several other non-parametric algorithms that target gene interactions. One frequently used method is the Multi-Dimension-Reductoin method (MDR). There are several differences as well as similarities between the Pattern Examiner^TM method and MDR.

First, MDR uses a cross-validation scheme to evaluate high-order interactions among markers, while Pattern Examiner^TM uses a chi-square-based test statistics, followed by Monte Carlo simulations. Second, MDR reports only the top set of genetic factors that together is most predictive of the disease outcome, while Pattern Examiner^TM identifies all potentially relevant associations, which frequently serve as internal controls for each other. Third, MDR analyzes genotype data only, while Pattern Examiner^TM simultaneously evaluates the contribution of alleles and genotypes to disease association. Fourth, MDR has been mostly used on candidate gene-based association analysis, while Pattern Examiner can be used for both candidate gene-based association analysis and whole-genome association analysis. Fifth, it was reported that sometimes missing data and low cell counts affect MDR's performance. Pattern Examiner takes missing data and low cell count into consideration when performing pattern discovery and statistical evaluation.