title: A new Bayesian approach incorporating covariate information for heterogeneity and its comparison with HLOD.
abstract: We consider a new Bayesian approach for heterogeneity that can take into account categorical covariates, if available. We use the Genetic Analysis Workshop 14 simulated data to first compare the Bayesian approach with the heterogeneity LOD, when no covariate information is used. We find that the former is more powerful, while the two approaches have comparable false-positive rates. We then include informative covariates in the Bayesian approach and find that it tends to give more precise interval estimates of the disease gene location than when covariates are not included. We had knowledge of the simulation models at the time we performed the analyses.
authors.affiliation: Department of Biostatistics, The University of North Texas Health Sciences Center, Fort Worth, TX 76107-2699, USA. sbiswas@hsc.unt.edu
authors.forename: Swati
authors.initials: S
authors.lastname: Biswas
authors.forename: Shili
authors.initials: S
authors.lastname: Lin
authors.forename: Donald A
authors.initials: DA
authors.lastname: Berry
mesh_terms: D001499:Bayes Theorem; D002877:Chromosomes, Human / Q000235:genetics; D018740:Genetic Heterogeneity; D008040:Genetic Linkage; D005828:Genetics, Population; D006801:Humans; D008126:Lod Score; D015203:Reproducibility of Results