title: Linkage and association analysis in pedigrees from different populations.
abstract: Using the Genetic Analysis Workshop 14 simulated datasets we carried out nonparametric linkage analyses and applied a log-linear method for analysis of case-parent-triad data with stratification on parental mating type. We proposed and applied a random effect modelling approach to explore the impact of population heterogeneity on tests of association between genetic markers and disease status. The estimated genetic effect may appear to be strongly significant in one population but nonsignificant in another population, leading to confusion about interpretation. However, when results are interpreted in the light of a random effects model, both studies may be making similar statements about a genetic effect that varies depending on environment and background.
authors.affiliation: Program in Population Health Sciences, Research Institute, Hospital for Sick Children, 555 University Avenue, Toronto, Ontario, M5G 1X8, Canada. joseph@utstat.toronto.edu
authors.forename: Joseph
authors.initials: J
authors.lastname: Beyene
authors.forename: Jun
authors.initials: J
authors.lastname: Yan
authors.forename: Celia M T
authors.initials: CM
authors.lastname: Greenwood
mesh_terms: D002877:Chromosomes, Human / Q000235:genetics; D002893:Chromosomes, Human, Pair 3 / Q000235:genetics; D008040:Genetic Linkage; D005819:Genetic Markers; D005828:Genetics, Population; D055106:Genome-Wide Association Study; D006801:Humans; D016014:Linear Models; D018895:Microsatellite Repeats / Q000235:genetics; D010375:Pedigree; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D018709:Statistics, Nonparametric
chemical_list: D005819:Genetic Markers