The pattern of linkage disequilibrium between a disease locus and a se
t of marker loci has been shown to be a useful tool for geneticists se
arching for disease genes. Several methods have been advanced to utili
ze the pairwise disequilibrium between the disease locus and each of a
set of marker loci. However, none of the methods take into account th
e information from all pairs simultaneously while also modeling the va
riability in the disequilibrium values due to the evolutionary dynamic
s of the population. We propose a Composite Likelihood (CL) model that
has these features when the physical distances between the marker loc
i are known or can be approximated. In this instance, and assuming tha
t there is a single disease mutation, the CL model depends on only thr
ee parameters, the recombination fraction between the disease locus an
d an arbitrary marker locus, theta, the age of the mutation, and a var
iance parameter. When the CL is maximized over a grid of theta, it pro
vides a graph that can direct the search for the disease locus. We als
o show how the CL model can be generalized to account for multiple dis
ease mutations. Evolutionary simulations demonstrate the power of the
analyses, as well as their potential weaknesses. Finally, we analyze t
he data from two mapped diseases, cystic fibrosis and diastrophic dysp
lasia, finding that the CL method performs well in both cases. (C) 199
6 Academic Press, Inc.