Multipoint linkage analysis via Metropolis jumping kernels.

S Lin

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PubMed · 8962460

Multipoint linkage analysis via Metropolis jumping kernels.

S Lin

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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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Algorithms Alleles Biometry Female Genetic Linkage Genetics, Medical Genotype Humans Likelihood Functions Lod Score Male Markov Chains Monte Carlo Method Phenotype Journal Article Research Support, U.S. Gov't, P.H.S.

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S Lin. 1996. Multipoint linkage analysis via Metropolis jumping kernels.. https://pubmed.ncbi.nlm.nih.gov/8962460/

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