Variance components/major locus likelihood approximation for quantitative, polychotomous, and multivariate data.
Pearson [Philos Trans R Soc Lond [A] 200:1-66, 1903], Mendell and Elston [Biometrics 30:41-57, 1974], and Rice et al. [Biometrics 35:451-459, 1979] approximated the likelihood of the multifactorial model on a dichotomous phenotype by a procedure of successive univariate computation and conditioning. Hasstedt [Pap: Pedigree Analysis Package, Rev. 3. 1989] and Demenais [Am J Hum Genet 49:773-785, 1991] extended the algorithm to include a major locus. Here I extend the algorithm to polychotomous, quantitative, and multivariate phenotypes, add a major locus to the model, and describe and evaluate the accuracy of an approximation of the resulting variance components/major locus model.
Hasstedt
S J
SJ
Department of Human Genetics, University of Utah, Salt Lake City 84112.
D000465:Algorithms; D002784:Cholesterol / Q000097:blood; D003327:Coronary Disease / Q000097:blood / Q000652:urine; D006801:Humans; D007610:Kallikreins / Q000652:urine; D016013:Likelihood Functions; D008957:Models, Genetic; D009765:Obesity / Q000097:blood / Q000652:urine; D010375:Pedigree; D010641:Phenotype
D002784:Cholesterol; D007610:Kallikreins