Family-based methods which rely on association for the mapping of genes in human populations

Abstract

Family-based tests, that employ association between alleles at a marker locus and a trait locus, have proven useful for the localization of genes in human genomes. Many existing tests have been derived as extensions of the transmission/disequilibrium test (TDT), which was originally introduced as a test of linkage in the presence of association for a susceptibility locus. One of these tests, the sib-TDT or S-TDT, makes use of genetic information from sibships containing at least one diseased and nondiseased child and is defined for a biallelic marker. We propose an extension of the S-TDT to a multiallelic marker and provide evidence that the chi-square distribution can be used to measure statistical signicance. The test is compared to three contemporary extensions for a multiallelic marker. We also present a test for a multiallelic marker that combines data from families with and without parental genetic information.

Next, tests of linkage and association are developed for a quantitative trait that utilize families, without restrictions on the number of children per family that can be used in the analysis. Tests are introduced that can be used on family data with parent and child genotypes, only child genotypes, or a combination of these types of families. Equations are derived that allow one to determine the sample size needed to achieve desired power. Through simulation, we demonstrate that existing tests have an elevated false-positive rate, when the size restrictions are not followed, and that a good deal of information is lost by adhering to the size restrictions. Permutation procedures are introduced that are recommended for small samples, but can also be used for extensions of the tests to multiallelic markers and to the simultaneous use of more than one marker.

Finally, resampling procedures for existing tests are explored. The resampling procedures reduce families to contain the number of children allowable for a valid test of linkage and association. We show that our tests are equivalent to the use of within cluster resampling for the existing tests, but that differences exist when resampling is performed on the basis of phenotypically extreme individuals.