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Identity-by-Descent-Based Phasing and Imputation in Founder Populations Using Graphical Models

Accurate knowledge of haplotypes, the combination of alleles co-residing on a single copy of a chromosome, enables powerful gene mapping and sequence imputation methods. Since humans are diploid, haplotypes must be derived from genotypes by a phasing process. In this study, we present a new computat...

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Detalles Bibliográficos
Autores principales: Palin, Kimmo, Campbell, Harry, Wright, Alan F, Wilson, James F, Durbin, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wiley Subscription Services, Inc., A Wiley Company 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3368215/
https://www.ncbi.nlm.nih.gov/pubmed/22006673
http://dx.doi.org/10.1002/gepi.20635
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author Palin, Kimmo
Campbell, Harry
Wright, Alan F
Wilson, James F
Durbin, Richard
author_facet Palin, Kimmo
Campbell, Harry
Wright, Alan F
Wilson, James F
Durbin, Richard
author_sort Palin, Kimmo
collection PubMed
description Accurate knowledge of haplotypes, the combination of alleles co-residing on a single copy of a chromosome, enables powerful gene mapping and sequence imputation methods. Since humans are diploid, haplotypes must be derived from genotypes by a phasing process. In this study, we present a new computational model for haplotype phasing based on pairwise sharing of haplotypes inferred to be Identical-By-Descent (IBD). We apply the Bayesian network based model in a new phasing algorithm, called systematic long-range phasing (SLRP), that can capitalize on the close genetic relationships in isolated founder populations, and show with simulated and real genome-wide genotype data that SLRP substantially reduces the rate of phasing errors compared to previous phasing algorithms. Furthermore, the method accurately identifies regions of IBD, enabling linkage-like studies without pedigrees, and can be used to impute most genotypes with very low error rate. Genet. Epidemiol. 2011. © 2011 Wiley Periodicals, Inc.35:853-860, 2011
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spelling pubmed-33682152012-06-06 Identity-by-Descent-Based Phasing and Imputation in Founder Populations Using Graphical Models Palin, Kimmo Campbell, Harry Wright, Alan F Wilson, James F Durbin, Richard Genet Epidemiol Original Articles Accurate knowledge of haplotypes, the combination of alleles co-residing on a single copy of a chromosome, enables powerful gene mapping and sequence imputation methods. Since humans are diploid, haplotypes must be derived from genotypes by a phasing process. In this study, we present a new computational model for haplotype phasing based on pairwise sharing of haplotypes inferred to be Identical-By-Descent (IBD). We apply the Bayesian network based model in a new phasing algorithm, called systematic long-range phasing (SLRP), that can capitalize on the close genetic relationships in isolated founder populations, and show with simulated and real genome-wide genotype data that SLRP substantially reduces the rate of phasing errors compared to previous phasing algorithms. Furthermore, the method accurately identifies regions of IBD, enabling linkage-like studies without pedigrees, and can be used to impute most genotypes with very low error rate. Genet. Epidemiol. 2011. © 2011 Wiley Periodicals, Inc.35:853-860, 2011 Wiley Subscription Services, Inc., A Wiley Company 2011-12 2011-10-17 /pmc/articles/PMC3368215/ /pubmed/22006673 http://dx.doi.org/10.1002/gepi.20635 Text en © 2011 Wiley Periodicals, Inc. http://creativecommons.org/licenses/by/2.5/ Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation.
spellingShingle Original Articles
Palin, Kimmo
Campbell, Harry
Wright, Alan F
Wilson, James F
Durbin, Richard
Identity-by-Descent-Based Phasing and Imputation in Founder Populations Using Graphical Models
title Identity-by-Descent-Based Phasing and Imputation in Founder Populations Using Graphical Models
title_full Identity-by-Descent-Based Phasing and Imputation in Founder Populations Using Graphical Models
title_fullStr Identity-by-Descent-Based Phasing and Imputation in Founder Populations Using Graphical Models
title_full_unstemmed Identity-by-Descent-Based Phasing and Imputation in Founder Populations Using Graphical Models
title_short Identity-by-Descent-Based Phasing and Imputation in Founder Populations Using Graphical Models
title_sort identity-by-descent-based phasing and imputation in founder populations using graphical models
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3368215/
https://www.ncbi.nlm.nih.gov/pubmed/22006673
http://dx.doi.org/10.1002/gepi.20635
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