title: Using overall allele-sharing to detect the presence of large-scale data errors and parameter misspecification in sib-pair linkage studies.
abstract: Data errors and marker allele frequency misspecification can lead to incorrect inference in linkage analysis. Here we demonstrate the effect of each on an allele-sharing statistic in a sample of sib pairs. In the context of relationship testing, we propose a new test that compares the sample genome-wide sib-pair allele sharing to its expectation and show that this test can detect the presence of large-scale data and model errors.
authors.affiliation: Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio 44106-7281, USA.
authors.forename: Jane M
authors.initials: JM
authors.lastname: Olson
authors.forename: Yeunjoo
authors.initials: Y
authors.lastname: Song
authors.forename: Qing
authors.initials: Q
authors.lastname: Lu
authors.forename: Geoffrey C
authors.initials: GC
authors.lastname: Wedig
authors.forename: Katrina A B
authors.initials: KA
authors.lastname: Goddard
mesh_terms: D000483:Alleles; D000544:Alzheimer Disease; D030541:Databases, Genetic; D005787:Gene Frequency; D008040:Genetic Linkage; D005838:Genotype; D006801:Humans; D016555:Matched-Pair Analysis; D015233:Models, Statistical; D035781:Siblings