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PMID: 15588497 Published · ppublish English Journal Article Review

A survey of current Bayesian gene mapping methods.

Human genomics ·Vol. 1 ·No. 5 ·2004-08-00 ·Pages 371-4

Molitor J, Marjoram P, Conti D, Thomas D

Abstract

Recently, there has been much interest in the use of Bayesian statistical methods for performing genetic analyses. Many of the computational difficulties previously associated with Bayesian analysis, such as multidimensional integration, can now be easily overcome using modern high-speed computers and Markov chain Monte Carlo (MCMC) methods. Much of this new technology has been used to perform gene mapping, especially through the use of multi-locus linkage disequilibrium techniques. This review attempts to summarise some of the currently available methods and the software available to implement these methods.

MeSH Terms
Bayes Theorem Chromosome Mapping Genetic Linkage Humans Models, Genetic Monte Carlo Method
Authors & Affiliations
4 authors, click to expand affiliations / ORCID
Molitor John
Department of Preventive Medicine, University of Southern California, 1540 Alcazar Street, CHP-220, Los Angeles, CA 90089-9011, USA. [email protected]
Marjoram Paul
Conti David
Thomas Duncan
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Article Info
Journal
Human genomics
Abbr.
Hum Genomics
ISSN
1473-9542
DOI
10.1186/1479-7364-1-5-371
Email
[email protected]
Published
2004-08-00
Pages
371-4
Language
English
Region
England
NLM ID
101202210
PMCID
PMC3525098
Subset
IM
External Links
PubMed source DOI: 10.1186/1479-7364-1-5-371 PMC Full Text View journal details
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