Multipoint linkage analysis via Metropolis jumping kernels.

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

Biometrics

journal_title

Biometrics

authors

Lin S

subject

Has Abstract

pub_date

1996-12-01 00:00:00

pages

1417-27

issue

4

eissn

0006-341X

issn

1541-0420

journal_volume

52

pub_type

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