title: Equivalence between Haseman-Elston and variance-components linkage analyses for sib pairs.
abstract: The Haseman-Elston regression method offers a simpler alternative to variance-components (VC) models, for the linkage analysis of quantitative traits. However, even the "revisited" method, which uses the cross-product--rather than the squared difference--in sib trait values, is, in general, less powerful than VC models. In this report, we clarify the relative efficiencies of existing Haseman-Elston methods and show how a new Haseman-Elston method can be constructed to have power equivalent to that of VC models. This method uses as the dependent variable a linear combination of squared sums and squared differences, in which the weights are determined by the overall trait correlation between sibs in a population. We show how this method can be used for both the selection of maximally informative sib pairs for genotyping and the subsequent analysis of such selected samples.
authors.affiliation: Social, Genetic & Developmental Research Centre, Institute of Psychiatry, London, SE5 8AF, England. p.sham@iop.kcl.ac.uk
authors.forename: P C
authors.initials: PC
authors.lastname: Sham
authors.forename: S
authors.initials: S
authors.lastname: Purcell
mesh_terms: D016009:Chi-Square Distribution; D002874:Chromosome Mapping / Q000379:methods* / Q000706:statistics & numerical data*; D003198:Computer Simulation; D008040:Genetic Linkage / Q000235:genetics*; D005838:Genotype; D006801:Humans; D016555:Matched-Pair Analysis; D009679:Nuclear Family; D019655:Quantitative Trait, Heritable; D012044:Regression Analysis