title: The advantages of dense marker sets for linkage analysis with very large families.
abstract: Dense sets of hundreds of thousands of markers have been developed for genome-wide association studies. These marker sets are also beneficial for linkage analysis of large, deep pedigrees containing distantly related cases. It is impossible to analyse jointly all genotypes in large pedigrees using the Lander-Green Algorithm, however, as marker density increases it becomes less crucial to analyse all individuals' genotypes simultaneously. In this report, an approximate multipoint non-parametric technique is described, where large pedigrees are split into many small pedigrees, each containing just two cases. This technique is demonstrated, using phased data from the International Hapmap Project to simulate sets of 10,000, 50,000 and 250,000 markers, showing that it becomes increasingly accurate as more markers are genotyped. This method allows routine linkage analysis of large families with dense marker sets and represents a more easily applied alternative to Monte Carlo Markov Chain methods.
authors.affiliation: Menzies Research Institute, University of Tasmania, Private Bag 23, Hobart, TAS, 7001, Australia. Russell.Thomson@utas.edu.au
authors.forename: Russell
authors.initials: R
authors.lastname: Thomson
authors.forename: Stephen
authors.initials: S
authors.lastname: Quinn
authors.forename: James
authors.initials: J
authors.lastname: McKay
authors.forename: Jeremy
authors.initials: J
authors.lastname: Silver
authors.forename: Melanie
authors.initials: M
authors.lastname: Bahlo
authors.forename: Liesel
authors.initials: L
authors.lastname: FitzGerald
authors.forename: Simon
authors.initials: S
authors.lastname: Foote
authors.forename: Jo
authors.initials: J
authors.lastname: Dickinson
authors.forename: Jim
authors.initials: J
authors.lastname: Stankovich
mesh_terms: D005190:Family; D008040:Genetic Linkage; D005819:Genetic Markers; D005821:Genetic Techniques; D006801:Humans; D008957:Models, Genetic; D010375:Pedigree; D015203:Reproducibility of Results; D013223:Statistics as Topic
chemical_list: D005819:Genetic Markers