I used the Java implementation of MDR to analyse 6113 SNPs passing a single-locus p value threshold of 0.01 in the WTCCC Crohn's and control data, with missing (incomplete) genotypes imputed as described in the legend to . Examination of all pairwise combinations in the entire 6113 SNP set proved computationally prohibitive but analysis via use of a prior filtering step with ReliefF or TuRF, which reduced the data set for MDR analysis to 1000 SNPs, was achievable. The best single-locus model identified was rs4471699, providing testing accuracy of 0.5852 and cross validation consistency of 10/10. The best two-locus model identified was rs4471699 and rs2076756, providing testing accuracy of 0.5879 and cross validation consistency of 4/10. MDR, in common with the other methods investigated, has clearly been dominated by the false positive result at rs4471699. Interestingly, however, this SNP is not selected by TuRF when filtering down the set of SNPs for MDR analysis to include only 100 SNPs. With the 100 SNP set, the best single-locus model identified was rs931058, providing testing accuracy of 0.5114 and cross validation consistency of 5/10. The best two-locus model identified was rs931058 and rs10824773, providing testing accuracy of 0.5205 but cross validation consistency of only 2/10. With the 100 SNP set it was computationally feasible to fit 3-locus and 4-locus models, however the resulting best models had similarly low cross validation consistencies. I also found extreme sensitivity (in both TuRF and MDR) to the choice of random number seed (data not shown), suggesting that, overall, these results should be interpreted with caution. A problem with MDR is that it outputs only the ‘best’ model rather than a measure of significance for all models or variables considered. Some idea of the ‘importance’ of variables can be determined by examining the ‘fitness landscape’ output from the program, shown here. Panel A: Fitness landscape scores from TuRF analysis of all 6113 SNPs Panel B: Fitness landscape scores from MDR analysis using top 1000 out of 6113 SNPs (filtered using TuRF) Panel C: Results from single-locus association analysis of all 6113 SNPs using the trend test implemented in PLINK. It is unclear whether the fitness landscape results from TuRF (Panel A) or MDR (Panel B) offer any great advantage over standard single-locus analysis (Panel C) with respect to determining the importance of variables.