title: Genome scanning for linkage: an overview.
abstract: Several different methods for linkage analysis are shown to arise from a single likelihood function L for the observed allele-sharing data at multiple markers in a chromosomal region. These include classical parametric lod score methods, nonparametric or "model-free" affected pedigree-member (APM) methods, and the Gaussian process method. Setting the methods in the context of the likelihood function L clarifies their underlying assumptions. A test statistic derived from L, the efficient score statistic, is introduced. It is asymptotically equivalent to the lod score, but it can be easier to compute when the penetrances and frequencies of alleles of the trait gene are not known. APM test statistics and the Gaussian lod score are shown to be special cases of efficient score statistics. This unified framework facilitates exploration of a range of models for the effects of a putative trait-predisposing gene, and it facilitates sensitivity analyses to examine the consequences of model misspecification.
authors: Department of Health Research and Policy, Stanford University School of Medicine, CA, USA. asw@osiris.stanford.edu
authors: A S
authors: AS
authors: Whittemore
mesh_terms: D005260:Female; D008040:Genetic Linkage; D015894:Genome, Human; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D008957:Models, Genetic; D015999:Multivariate Analysis; D016011:Normal Distribution; D010375:Pedigree; D018709:Statistics, Nonparametric