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Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel
Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low depth...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Pub. Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4579394/ https://www.ncbi.nlm.nih.gov/pubmed/26368830 http://dx.doi.org/10.1038/ncomms9111 |
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author | Huang, Jie Howie, Bryan McCarthy, Shane Memari, Yasin Walter, Klaudia Min, Josine L. Danecek, Petr Malerba, Giovanni Trabetti, Elisabetta Zheng, Hou-Feng Gambaro, Giovanni Richards, J. Brent Durbin, Richard Timpson, Nicholas J. Marchini, Jonathan Soranzo, Nicole |
author_facet | Huang, Jie Howie, Bryan McCarthy, Shane Memari, Yasin Walter, Klaudia Min, Josine L. Danecek, Petr Malerba, Giovanni Trabetti, Elisabetta Zheng, Hou-Feng Gambaro, Giovanni Richards, J. Brent Durbin, Richard Timpson, Nicholas J. Marchini, Jonathan Soranzo, Nicole |
author_sort | Huang, Jie |
collection | PubMed |
description | Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low depth (average 7x), aiming to exhaustively characterize genetic variation down to 0.1% minor allele frequency in the British population. Here we demonstrate the value of this resource for improving imputation accuracy at rare and low-frequency variants in both a UK and an Italian population. We show that large increases in imputation accuracy can be achieved by re-phasing WGS reference panels after initial genotype calling. We also present a method for combining WGS panels to improve variant coverage and downstream imputation accuracy, which we illustrate by integrating 7,562 WGS haplotypes from the UK10K project with 2,184 haplotypes from the 1000 Genomes Project. Finally, we introduce a novel approximation that maintains speed without sacrificing imputation accuracy for rare variants. |
format | Online Article Text |
id | pubmed-4579394 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Pub. Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-45793942015-10-01 Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel Huang, Jie Howie, Bryan McCarthy, Shane Memari, Yasin Walter, Klaudia Min, Josine L. Danecek, Petr Malerba, Giovanni Trabetti, Elisabetta Zheng, Hou-Feng Gambaro, Giovanni Richards, J. Brent Durbin, Richard Timpson, Nicholas J. Marchini, Jonathan Soranzo, Nicole Nat Commun Article Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low depth (average 7x), aiming to exhaustively characterize genetic variation down to 0.1% minor allele frequency in the British population. Here we demonstrate the value of this resource for improving imputation accuracy at rare and low-frequency variants in both a UK and an Italian population. We show that large increases in imputation accuracy can be achieved by re-phasing WGS reference panels after initial genotype calling. We also present a method for combining WGS panels to improve variant coverage and downstream imputation accuracy, which we illustrate by integrating 7,562 WGS haplotypes from the UK10K project with 2,184 haplotypes from the 1000 Genomes Project. Finally, we introduce a novel approximation that maintains speed without sacrificing imputation accuracy for rare variants. Nature Pub. Group 2015-09-14 /pmc/articles/PMC4579394/ /pubmed/26368830 http://dx.doi.org/10.1038/ncomms9111 Text en Copyright © 2015, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Huang, Jie Howie, Bryan McCarthy, Shane Memari, Yasin Walter, Klaudia Min, Josine L. Danecek, Petr Malerba, Giovanni Trabetti, Elisabetta Zheng, Hou-Feng Gambaro, Giovanni Richards, J. Brent Durbin, Richard Timpson, Nicholas J. Marchini, Jonathan Soranzo, Nicole Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel |
title | Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel |
title_full | Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel |
title_fullStr | Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel |
title_full_unstemmed | Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel |
title_short | Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel |
title_sort | improved imputation of low-frequency and rare variants using the uk10k haplotype reference panel |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4579394/ https://www.ncbi.nlm.nih.gov/pubmed/26368830 http://dx.doi.org/10.1038/ncomms9111 |
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