Multipoint linkage analysis via Metropolis jumping kernels
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Updated: Nov 3, 2026

Cross-Modal Multivariate Pattern Analysis
Published on: November 9, 2011
1Department of Statistics, Ohio State University, Columbus 43210, USA.
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.
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