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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wiley Subscription Services, Inc., A Wiley Company
2011
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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 |
format | Online Article Text |
id | pubmed-3368215 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Wiley Subscription Services, Inc., A Wiley Company |
record_format | MEDLINE/PubMed |
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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