In the proposed method, the idea of correcting the variance using genomic data is similar to the idea behind Genomic Control (GC) [Devlin and Roeder, 1999]. Both approaches use a constant correction for tests based on all genome markers. However, GC corrects the test statistics after inflated test statistics are observed, while the proposed method uses the genome data to adjust the variance so that the test statistic is not inflated in the first place. This also explains why the proposed test is straightforward for more complicated markers such as multiallelic markers, while GC needs separate correction factors for each type of marker, defined by the number of alleles. GC suffers when used for multiallelic markers because a separate correction for each type of marker is needed, and because a large number of markers of each type of marker are required to achieve an adequate correction [Marchini et al., 2004]. In general, multiallelic markers or haplotypes based on multiple SNPs can be considerably more informative than diallelic markers for association testing [Ott and Rabinowitz, 1997; Chapman and Wijsman, 1998]. For
