title: A test for linkage and association in general pedigrees: the pedigree disequilibrium test.
abstract: Family-based tests of linkage disequilibrium typically are based on nuclear-family data including affected individuals and their parents or their unaffected siblings. A limitation of such tests is that they generally are not valid tests of association when data from related nuclear families from larger pedigrees are used. Standard methods require selection of a single nuclear family from any extended pedigrees when testing for linkage disequilibrium. Often data are available for larger pedigrees, and it would be desirable to have a valid test of linkage disequilibrium that can use all potentially informative data. In this study, we present the pedigree disequilibrium test (PDT) for analysis of linkage disequilibrium in general pedigrees. The PDT can use data from related nuclear families from extended pedigrees and is valid even when there is population substructure. Using computer simulations, we demonstrated validity of the test when the asymptotic distribution is used to assess the significance, and examined statistical power. Power simulations demonstrate that, when extended pedigree data are available, substantial gains in power can be attained by use of the PDT rather than existing methods that use only a subset of the data. Furthermore, the PDT remains more powerful even when there is misclassification of unaffected individuals. Our simulations suggest that there may be advantages to using the PDT even if the data consist of independent families without extended family information. Thus, the PDT provides a general test of linkage disequilibrium that can be widely applied to different data structures.
authors.affiliation: Center for Human Genetics, Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA. emartin@chg.mc.duke.edu
authors.forename: E R
authors.initials: ER
authors.lastname: Martin
authors.forename: S A
authors.initials: SA
authors.lastname: Monks
authors.forename: L L
authors.initials: LL
authors.lastname: Warren
authors.forename: N L
authors.initials: NL
authors.lastname: Kaplan
mesh_terms: D000483:Alleles; D002874:Chromosome Mapping / Q000379:methods* / Q000706:statistics & numerical data*; D003198:Computer Simulation; D005260:Female; D030342:Genetic Diseases, Inborn / Q000453:epidemiology / Q000235:genetics; D005838:Genotype; D006801:Humans; D015810:Linkage Disequilibrium / Q000235:genetics*; D008297:Male; D008957:Models, Genetic; D009679:Nuclear Family; D010375:Pedigree; D019683:Penetrance; D015995:Prevalence; D015203:Reproducibility of Results; D012107:Research Design; D018401:Sample Size; D016008:Statistical Distributions