title: Two-locus modeling of asthma in a Hutterite pedigree via Markov chain Monte Carlo.
abstract: Bayesian Markov chain Monte Carlo (MCMC) segregation analysis for asthma was performed on the whole 1,544-member Hutterite pedigree. Heterogeneous and epistatic two-locus models and complex one-locus models were investigated, with trait loci postulated to be linked to markers in regions previously found to be possibly linked to asthma or atopy. The epistatic two-locus dominant-dominant model provided the best estimates, among the models investigated, in terms of prediction of population prevalence and relative risk for sibs of the affected.
authors.affiliation: Department of Statistics, Ohio State University, 1958 Neil Avenue, Columbus, OH 43210, USA.
authors.forename: Y
authors.initials: Y
authors.lastname: Luo
authors.forename: S
authors.initials: S
authors.lastname: Lin
authors.forename: M E
authors.initials: ME
authors.lastname: Irwin
mesh_terms: D001249:Asthma / Q000453:epidemiology / Q000235:genetics*; D001499:Bayes Theorem; D002648:Child; D002874:Chromosome Mapping; D002893:Chromosomes, Human, Pair 3; D002895:Chromosomes, Human, Pair 5; D003241:Consanguinity; D003430:Cross-Sectional Studies; D005828:Genetics, Population; D006801:Humans; D008390:Markov Chains; D008957:Models, Genetic; D009010:Monte Carlo Method; D012130:Respiratory Hypersensitivity / Q000453:epidemiology / Q000235:genetics; D012306:Risk; D013023:South Dakota