title: Covariates in linkage analysis using sibling and cousin pairs.
abstract: Using simulated data from GAW 12, problem 2, we further develop a novel technique to detect and use significant covariates in linkage analysis. The method, first introduced by Rice et al. [Genet Epidemiol 17(Suppl. 1):S691-5, 1999], uses logistic regression to model perturbation in sharing as a function of covariate levels. The original method allows use of all sib pairs (concordant affected, concordant unaffected, and discordant). Here we extend this method to include cousin pairs in analysis.
authors.affiliation: Department of Psychiatry, Washington University School of Medicine, 660 South Euclid Avenue, Box 8134, St. Louis, MO 63110, USA.
authors.forename: N L
authors.initials: NL
authors.lastname: Saccone
authors.forename: N
authors.initials: N
authors.lastname: Rochberg
authors.forename: R J
authors.initials: RJ
authors.lastname: Neuman
authors.forename: J P
authors.initials: JP
authors.lastname: Rice
mesh_terms: D000328:Adult; D000483:Alleles; D000704:Analysis of Variance; D002648:Child; D002874:Chromosome Mapping / Q000706:statistics & numerical data*; D005260:Female; D006580:Genetic Carrier Screening; D005819:Genetic Markers / Q000235:genetics; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D005838:Genotype; D006801:Humans; D016015:Logistic Models; D008297:Male; D008957:Models, Genetic
chemical_list: D005819:Genetic Markers