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A survey of current Bayesian gene mapping method
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 a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2004
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3525098/ https://www.ncbi.nlm.nih.gov/pubmed/15588497 http://dx.doi.org/10.1186/1479-7364-1-5-371 |
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author | Molitor, John Marjoram, Paul Conti, David Thomas, Duncan |
author_facet | Molitor, John Marjoram, Paul Conti, David Thomas, Duncan |
author_sort | Molitor, John |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3525098 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2004 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35250982013-01-10 A survey of current Bayesian gene mapping method Molitor, John Marjoram, Paul Conti, David Thomas, Duncan Hum Genomics Software Review 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. BioMed Central 2004-08-01 /pmc/articles/PMC3525098/ /pubmed/15588497 http://dx.doi.org/10.1186/1479-7364-1-5-371 Text en Copyright ©2004 Henry Stewart Publications |
spellingShingle | Software Review Molitor, John Marjoram, Paul Conti, David Thomas, Duncan A survey of current Bayesian gene mapping method |
title | A survey of current Bayesian gene mapping method |
title_full | A survey of current Bayesian gene mapping method |
title_fullStr | A survey of current Bayesian gene mapping method |
title_full_unstemmed | A survey of current Bayesian gene mapping method |
title_short | A survey of current Bayesian gene mapping method |
title_sort | survey of current bayesian gene mapping method |
topic | Software Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3525098/ https://www.ncbi.nlm.nih.gov/pubmed/15588497 http://dx.doi.org/10.1186/1479-7364-1-5-371 |
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