Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Molitor, John, Marjoram, Paul, Conti, David, Thomas, Duncan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2004
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
_version_ 1782253393349181440
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
work_keys_str_mv AT molitorjohn asurveyofcurrentbayesiangenemappingmethod
AT marjorampaul asurveyofcurrentbayesiangenemappingmethod
AT contidavid asurveyofcurrentbayesiangenemappingmethod
AT thomasduncan asurveyofcurrentbayesiangenemappingmethod
AT molitorjohn surveyofcurrentbayesiangenemappingmethod
AT marjorampaul surveyofcurrentbayesiangenemappingmethod
AT contidavid surveyofcurrentbayesiangenemappingmethod
AT thomasduncan surveyofcurrentbayesiangenemappingmethod