Abstract:
:Multipoint linkage analysis is being performed routinely in medical genetic studies to localize disease genes. This likelihood-based method is very computationally intensive. Exact computations are thus formidable for problems with large number of genetic markers and complex pedigrees. This paper proposes a Monte Carlo method to estimate the required likelihoods. The space of multilocus genotypes is sampled using a hybrid algorithm with a mixture of Gibbs samplers and Metropolis jumping kernels. These samples are essentially realizations of a Markov chain, and are distributed approximately according to the conditional genotype distribution given the observed phenotypic data. We present a simulation study with several eight-point analyses to demonstrate the feasibility of the current method.
journal_name
Biometricsjournal_title
Biometricsauthors
Lin Ssubject
Has Abstractpub_date
1996-12-01 00:00:00pages
1417-27issue
4eissn
0006-341Xissn
1541-0420journal_volume
52pub_type
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