title: Joint modeling of linkage and association using affected sib-pair data.
abstract: There has been a growing interest in developing strategies for identifying single-nucleotide polymorphisms (SNPs) that explain a linkage signal by joint modeling of linkage and association. We compare several existing methods and propose a new method called the homozygote sharing transmission-disequilibrium test (HSTDT) to detect linkage and association or to identify SNPs explaining the linkage signal on chromosome 6 for rheumatoid arthritis using 100 replicates of the Genetic Analysis Workshop (GAW) 15 simulated affected sib-pair data. Existing methods considered included the family-based tests of association implemented in FBAT, a transmission-disequilibrium test, a conditional logistic regression approach, a likelihood-based approach implemented in LAMP, and the homozygote sharing test (HST). We compared the type I error rates and power for tests classified into three categories according to their null hypotheses: 1) no association in the presence of linkage (i.e., a SNP explains none of the linkage evidence), 2) no linkage adjusting for the association (i.e., a SNP explains all linkage evidence), and 3) no linkage and no association. For testing association in the presence of linkage, we found similar power among all tests except for the homozygote sharing test that had lower power. When testing linkage adjusting for association, similar power was observed between LAMP and HST, but lower power for the conditional logistic regression method. When testing linkage or association, the conditional logistic regression method was more powerful than FBAT.
authors.affiliation: Department of Mathematics and Statistics, Boston University, 111 Cummington Street, Boston, Massachusetts 02115, USA.
authors.forename: Ming-Huei
authors.initials: MH
authors.lastname: Chen
authors.affiliation: Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 221 Longwood Avenue 341G, Boston, Massachusetts 02115, USA.
authors.forename: Jing
authors.initials: J
authors.lastname: Cui
authors.affiliation: Department of Mathematics and Statistics, Boston University, 111 Cummington Street, Boston, Massachusetts 02115, USA.
authors.forename: Chao-Yu
authors.initials: CY
authors.lastname: Guo
authors.affiliation: Department of Biostatistics, Boston University School of Public Health, 715 Albany Street, Boston, Massachusetts 02118, USA.
authors.forename: L Adrienne
authors.initials: LA
authors.lastname: Cupples
authors.affiliation: Genizon BioSciences Inc., 880 McCaffrey, Montreal, Quebec H4T 2C7, Canada.
authors.forename: Paul
authors.initials: P
authors.lastname: Van Eerdewegh
authors.affiliation: Department of Biostatistics, Boston University School of Public Health, 715 Albany Street, Boston, Massachusetts 02118, USA.
authors.forename: Josée
authors.initials: J
authors.lastname: Dupuis
authors.affiliation: Department of Biostatistics, Boston University School of Public Health, 715 Albany Street, Boston, Massachusetts 02118, USA.
authors.forename: Qiong
authors.initials: Q
authors.lastname: Yang