Optimal Step Length EM Algorithm (OSLEM) for the estimation of haplotype frequency and its application in lipoprotein lipase genotyping

<p>Abstract</p> <p>Background</p> <p>Haplotype based linkage disequilibrium (LD) mapping has become a powerful and cost-effective method for performing genetic association studies, particularly in the search for genetic markers in linkage disequilibrium with complex dis...

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Main Authors: Morabia Alfredo, Sheng Huitao, Zhang Peisen, Gilliam T Conrad
Format: Article
Language:English
Published: BMC 2003-01-01
Series:BMC Bioinformatics
Subjects:
Online Access:http://www.biomedcentral.com/1471-2105/4/3
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spelling doaj-e28ff1f361704683a1c9c964d81a84082020-11-25T02:42:09ZengBMCBMC Bioinformatics1471-21052003-01-0141310.1186/1471-2105-4-3Optimal Step Length EM Algorithm (OSLEM) for the estimation of haplotype frequency and its application in lipoprotein lipase genotypingMorabia AlfredoSheng HuitaoZhang PeisenGilliam T Conrad<p>Abstract</p> <p>Background</p> <p>Haplotype based linkage disequilibrium (LD) mapping has become a powerful and cost-effective method for performing genetic association studies, particularly in the search for genetic markers in linkage disequilibrium with complex disease loci. Various methods (e.g. Monte-Carlo (Gibbs sampling); EM (expectation maximization); and Clark's method) have been used to estimate haplotype frequencies from routine genotyping data.</p> <p>Results</p> <p>These algorithms can be very slow for large number of SNPs. In order to speed them up, we have developed a new algorithm using numerical analysis technology, a so-called optimal step length EM (OSLEM) that accelerates the calculation. By optimizing approximately the step length of the EM algorithm, OSLEM can run at about twice the speed of EM. This algorithm has been used for lipoprotein lipase (LPL) genotyping analysis.</p> <p>Conclusions</p> <p>This new optimal step length EM (OSLEM) algorithm can accelerate the calculation for haplotype frequency estimation for genotyping data without pedigree information. An OSLEM on-line server is available, as well as a free downloadable version.</p> http://www.biomedcentral.com/1471-2105/4/3Haplotype frequency estimationExpectation Maximization AlgorithmGenotypeLipoprotein Lipase
collection DOAJ
language English
format Article
sources DOAJ
author Morabia Alfredo
Sheng Huitao
Zhang Peisen
Gilliam T Conrad
spellingShingle Morabia Alfredo
Sheng Huitao
Zhang Peisen
Gilliam T Conrad
Optimal Step Length EM Algorithm (OSLEM) for the estimation of haplotype frequency and its application in lipoprotein lipase genotyping
BMC Bioinformatics
Haplotype frequency estimation
Expectation Maximization Algorithm
Genotype
Lipoprotein Lipase
author_facet Morabia Alfredo
Sheng Huitao
Zhang Peisen
Gilliam T Conrad
author_sort Morabia Alfredo
title Optimal Step Length EM Algorithm (OSLEM) for the estimation of haplotype frequency and its application in lipoprotein lipase genotyping
title_short Optimal Step Length EM Algorithm (OSLEM) for the estimation of haplotype frequency and its application in lipoprotein lipase genotyping
title_full Optimal Step Length EM Algorithm (OSLEM) for the estimation of haplotype frequency and its application in lipoprotein lipase genotyping
title_fullStr Optimal Step Length EM Algorithm (OSLEM) for the estimation of haplotype frequency and its application in lipoprotein lipase genotyping
title_full_unstemmed Optimal Step Length EM Algorithm (OSLEM) for the estimation of haplotype frequency and its application in lipoprotein lipase genotyping
title_sort optimal step length em algorithm (oslem) for the estimation of haplotype frequency and its application in lipoprotein lipase genotyping
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2003-01-01
description <p>Abstract</p> <p>Background</p> <p>Haplotype based linkage disequilibrium (LD) mapping has become a powerful and cost-effective method for performing genetic association studies, particularly in the search for genetic markers in linkage disequilibrium with complex disease loci. Various methods (e.g. Monte-Carlo (Gibbs sampling); EM (expectation maximization); and Clark's method) have been used to estimate haplotype frequencies from routine genotyping data.</p> <p>Results</p> <p>These algorithms can be very slow for large number of SNPs. In order to speed them up, we have developed a new algorithm using numerical analysis technology, a so-called optimal step length EM (OSLEM) that accelerates the calculation. By optimizing approximately the step length of the EM algorithm, OSLEM can run at about twice the speed of EM. This algorithm has been used for lipoprotein lipase (LPL) genotyping analysis.</p> <p>Conclusions</p> <p>This new optimal step length EM (OSLEM) algorithm can accelerate the calculation for haplotype frequency estimation for genotyping data without pedigree information. An OSLEM on-line server is available, as well as a free downloadable version.</p>
topic Haplotype frequency estimation
Expectation Maximization Algorithm
Genotype
Lipoprotein Lipase
url http://www.biomedcentral.com/1471-2105/4/3
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