title: Power and robustness of a score test for linkage analysis of quantitative traits using identity by descent data on sib pairs.
abstract: Identification of genes involved in complex traits by traditional (lod score) linkage analysis is difficult due to many complicating factors. An unfortunate drawback of non-parametric procedures in general, though, is their low power to detect genetic effects. Recently, Dudoit and Speed [2000] proposed using a (likelihood-based) score test for detecting linkage with IBD data on sib pairs. This method uses the likelihood for theta, the recombination fraction between a trait locus and a marker locus, conditional on the phenotypes of the two sibs to test the null hypothesis of no linkage (theta = (1/2)). Although a genetic model must be specified, the approach offers several advantages. This paper presents results of simulation studies characterizing the power and robustness properties of this score test for linkage, and compares the power of the test to the Haseman-Elston and modified Haseman-Elston tests. The score test is seen to have impressively high power across a broad range of true and assumed models, particularly under multiple ascertainment. Assuming an additive model with a moderate allele frequency, in the range of p = 0.2 to 0.5, along with heritability H = 0.3 and a moderate residual correlation rho = 0.2 resulted in a very good overall performance across a wide range of trait-generating models. Generally, our results indicate that this score test for linkage offers a high degree of protection against wrong assumptions due to its strong robustness when used with the recommended additive model.
authors.affiliation: Department of Statistics, University of California at Los Angeles, Los Angeles, CA 90095-1554, USA. darlene@stat.ucla.edu
authors.forename: D R
authors.initials: DR
authors.lastname: Goldstein
authors.forename: S
authors.initials: S
authors.lastname: Dudoit
authors.forename: T P
authors.initials: TP
authors.lastname: Speed
mesh_terms: D003198:Computer Simulation; D008040:Genetic Linkage; D005826:Genetics, Medical; D006801:Humans; D008957:Models, Genetic; D019655:Quantitative Trait, Heritable