title: Relationship inference from trios of individuals, in the presence of typing error.
abstract: Misspecification of relationships and of genotype data can cause problems in linkage analyses based on genome-scan data. Previous reports have focused on pairwise relationships and a simple error model. This article considers the increased information available from the joint analysis of trios of individuals, integrating this analysis with an error model that allows for the most common genotyping errors. Given observed marker phenotypes in a genome scan, computational methods are outlined both for likelihoods of relationships and for the posterior probabilities of underlying genotypes. The methods are applied to examples from two real data sets: one has been previously well analyzed, and, hence, Mendelian inconsistencies have been removed; the other typifies the pedigree and genotype errors encountered in the initial analyses of a study. It is demonstrated that the coupling of relationship inference and error detection is quite effective, that the error model is computationally practical, and that data on a third relative can often clarify relationships.
authors.affiliation: Department of Statistics, University of Washington, Seattle, 98195, USA.
authors.forename: Solveig K
authors.initials: SK
authors.lastname: Sieberts
authors.forename: Ellen M
authors.initials: EM
authors.lastname: Wijsman
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Thompson
mesh_terms: D000437:Alcoholism / Q000235:genetics; D000465:Algorithms; D002874:Chromosome Mapping / Q000379:methods*; D005260:Female; D005819:Genetic Markers; D005838:Genotype; D006801:Humans; D020407:Internet; D016013:Likelihood Functions; D008297:Male; D009679:Nuclear Family; D010375:Pedigree; D012107:Research Design; D012984:Software; D014427:Twins / Q000235:genetics
chemical_list: D005819:Genetic Markers