There are a number of statistical methods that are designed to overcome this problem. When the entire genealogy of the sample is known, one suggested approach is to use the Armitage trend test with a correction factor that is computed conditional on the marker genotypes and pedigree structure [Slager and Schaid, 2001]. With the same idea, the standard χ2 test for comparing allele frequencies between cases and controls can be modified with a correction factor to account for relatedness among individuals (corrected χ2 test) [Bourgain et al., 2003]. This correction factor depends only on kinship and inbreeding coefficients derived directly from the pedigree information. While a modified Armitage trend test is not applicable to complicated pedigree structures, the corrected χ2 test can be used for any population structure for which kinship coefficients among pairs of individuals and inbreeding coefficients of every individual are known [Bourgain et al., 2003]. Furthermore, the χ2 test can be easily performed for multiallelic data, including the presence of rare alleles. To improve power, a quasi-likelihood score (QLS) test has also been proposed [Bourgain et al.,
