There is a high degree of correlation between many of the variants in a genome-wide association study due to linkage disequilibrium across the chromosomes. If we corrected for multiple testing using Bonferroni or False Discovery Rate (FDR), we would be discounting the correlation between the markers and over correcting our P value. Permutation testing allows us to maintain the correlation structure between the variants and calculate a global cut-off where any P values that are smaller than that observed value will have an experiment-wise significance. This approach allows the correlation among variants and is therefore less conservative than the Bonferroni approach. P values are reported for point-wise (nominal) significance and experiment-wise (corrected) significance.
