title: A multivariate approach to affected-sib-pair analysis using highly dense molecular maps.
abstract: A multivariate approach to affected-sib-pair analyses was performed to localize disease-susceptibility genes with a minimum number of type I errors (false positives). Using 1,155 independent affected sib pairs extracted from Problem 2A of the GAW10 data set, we were able to localize major genes (MG) 1 and 2. Using 30% of the affected-sib-pair sample (N = 337) we were able to localize MG1. False positives were not detected in either of these samples.
authors.affiliation: Department of Psychiatry, University of California Los Angeles, USA.
authors.forename: J N
authors.initials: JN
authors.lastname: Bailey
authors.forename: C G
authors.initials: CG
authors.lastname: Palmer
authors.forename: J A
authors.initials: JA
authors.lastname: Woodward
authors.forename: S L
authors.initials: SL
authors.lastname: Smalley
mesh_terms: D003198:Computer Simulation; D005260:Female; D030342:Genetic Diseases, Inborn / Q000175:diagnosis*; D020022:Genetic Predisposition to Disease; D006801:Humans; D008297:Male; D016555:Matched-Pair Analysis; D008957:Models, Genetic; D015999:Multivariate Analysis; D009679:Nuclear Family; D011237:Predictive Value of Tests