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Imputation in families using a heuristic phasing approach
Whole genome sequencing (WGS) remains prohibitively expensive, which has encouraged the development of methods to impute WGS data into nonsequenced individuals using a framework of single nucleotide polymorphisms genotyped for genome-wide association studies (GWAS). Although successful methods have...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143623/ https://www.ncbi.nlm.nih.gov/pubmed/25519369 http://dx.doi.org/10.1186/1753-6561-8-S1-S16 |
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author | Blackburn, August N Dean, Angela K Lehman, Donna M |
author_facet | Blackburn, August N Dean, Angela K Lehman, Donna M |
author_sort | Blackburn, August N |
collection | PubMed |
description | Whole genome sequencing (WGS) remains prohibitively expensive, which has encouraged the development of methods to impute WGS data into nonsequenced individuals using a framework of single nucleotide polymorphisms genotyped for genome-wide association studies (GWAS). Although successful methods have been developed for cohorts of unrelated individuals, current imputation methods in related individuals are limited by pedigree size, by the distance of relationships, or by computation time. In this article, we describe a method for imputation in arbitrarily shaped multigenerational pedigrees that can impute genotypes across distantly related individuals based on identity by descent. We evaluate this approach using GWAS data and apply this approach to WGS data distributed for Genetic Analysis Workshop 18. |
format | Online Article Text |
id | pubmed-4143623 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41436232014-09-02 Imputation in families using a heuristic phasing approach Blackburn, August N Dean, Angela K Lehman, Donna M BMC Proc Proceedings Whole genome sequencing (WGS) remains prohibitively expensive, which has encouraged the development of methods to impute WGS data into nonsequenced individuals using a framework of single nucleotide polymorphisms genotyped for genome-wide association studies (GWAS). Although successful methods have been developed for cohorts of unrelated individuals, current imputation methods in related individuals are limited by pedigree size, by the distance of relationships, or by computation time. In this article, we describe a method for imputation in arbitrarily shaped multigenerational pedigrees that can impute genotypes across distantly related individuals based on identity by descent. We evaluate this approach using GWAS data and apply this approach to WGS data distributed for Genetic Analysis Workshop 18. BioMed Central 2014-06-17 /pmc/articles/PMC4143623/ /pubmed/25519369 http://dx.doi.org/10.1186/1753-6561-8-S1-S16 Text en Copyright © 2014 Blackburn et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Proceedings Blackburn, August N Dean, Angela K Lehman, Donna M Imputation in families using a heuristic phasing approach |
title | Imputation in families using a heuristic phasing approach |
title_full | Imputation in families using a heuristic phasing approach |
title_fullStr | Imputation in families using a heuristic phasing approach |
title_full_unstemmed | Imputation in families using a heuristic phasing approach |
title_short | Imputation in families using a heuristic phasing approach |
title_sort | imputation in families using a heuristic phasing approach |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143623/ https://www.ncbi.nlm.nih.gov/pubmed/25519369 http://dx.doi.org/10.1186/1753-6561-8-S1-S16 |
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