Abstract

A disease-associated mutation arises on a single chromosome such that alleles at linked markers are initially in complete linkage disequilibrium (LD) with the mutation. LD can be used as a tool for high-resolution mapping of the position of a disease mutation relative to a set of linked marker loci. When more than two linked marker loci are considered, developing a maximum likelihood approach is a challenging mathematical problem. To reduce the complexity, approximate and composite likelihood (CL) methods have been developed for multipoint LD mapping that use simplified models of population history, or of recombination, that ignore some of the statistical dependence among disease chromosomes and among marker loci. We describe the relationship among several composite likelihood methods for multipoint LD mapping, and suggest an alternative CL method that takes better account of the statistical dependence among marker loci.

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