HapTree: a novel Bayesian framework for single individual polyplotyping using NGS data.

As the more recent next-generation sequencing (NGS) technologies provide longer read sequences, the use of sequencing datasets for complete haplotype phasing is fast becoming a reality, allowing haplotype reconstruction of a single sequenced genome. Nearly all previous haplotype reconstruction studi...

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Autores principales:	Emily Berger, Deniz Yorukoglu, Jian Peng, Bonnie Berger
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/9e44faa798804343b74dd345c48d6308
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spelling	oai:doaj.org-article:9e44faa798804343b74dd345c48d63082021-11-18T05:53:02ZHapTree: a novel Bayesian framework for single individual polyplotyping using NGS data.1553-734X1553-735810.1371/journal.pcbi.1003502https://doaj.org/article/9e44faa798804343b74dd345c48d63082014-03-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24675685/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358As the more recent next-generation sequencing (NGS) technologies provide longer read sequences, the use of sequencing datasets for complete haplotype phasing is fast becoming a reality, allowing haplotype reconstruction of a single sequenced genome. Nearly all previous haplotype reconstruction studies have focused on diploid genomes and are rarely scalable to genomes with higher ploidy. Yet computational investigations into polyploid genomes carry great importance, impacting plant, yeast and fish genomics, as well as the studies of the evolution of modern-day eukaryotes and (epi)genetic interactions between copies of genes. In this paper, we describe a novel maximum-likelihood estimation framework, HapTree, for polyploid haplotype assembly of an individual genome using NGS read datasets. We evaluate the performance of HapTree on simulated polyploid sequencing read data modeled after Illumina sequencing technologies. For triploid and higher ploidy genomes, we demonstrate that HapTree substantially improves haplotype assembly accuracy and efficiency over the state-of-the-art; moreover, HapTree is the first scalable polyplotyping method for higher ploidy. As a proof of concept, we also test our method on real sequencing data from NA12878 (1000 Genomes Project) and evaluate the quality of assembled haplotypes with respect to trio-based diplotype annotation as the ground truth. The results indicate that HapTree significantly improves the switch accuracy within phased haplotype blocks as compared to existing haplotype assembly methods, while producing comparable minimum error correction (MEC) values. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2-5.Emily BergerDeniz YorukogluJian PengBonnie BergerPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 10, Iss 3, p e1003502 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Emily Berger Deniz Yorukoglu Jian Peng Bonnie Berger HapTree: a novel Bayesian framework for single individual polyplotyping using NGS data.
description	As the more recent next-generation sequencing (NGS) technologies provide longer read sequences, the use of sequencing datasets for complete haplotype phasing is fast becoming a reality, allowing haplotype reconstruction of a single sequenced genome. Nearly all previous haplotype reconstruction studies have focused on diploid genomes and are rarely scalable to genomes with higher ploidy. Yet computational investigations into polyploid genomes carry great importance, impacting plant, yeast and fish genomics, as well as the studies of the evolution of modern-day eukaryotes and (epi)genetic interactions between copies of genes. In this paper, we describe a novel maximum-likelihood estimation framework, HapTree, for polyploid haplotype assembly of an individual genome using NGS read datasets. We evaluate the performance of HapTree on simulated polyploid sequencing read data modeled after Illumina sequencing technologies. For triploid and higher ploidy genomes, we demonstrate that HapTree substantially improves haplotype assembly accuracy and efficiency over the state-of-the-art; moreover, HapTree is the first scalable polyplotyping method for higher ploidy. As a proof of concept, we also test our method on real sequencing data from NA12878 (1000 Genomes Project) and evaluate the quality of assembled haplotypes with respect to trio-based diplotype annotation as the ground truth. The results indicate that HapTree significantly improves the switch accuracy within phased haplotype blocks as compared to existing haplotype assembly methods, while producing comparable minimum error correction (MEC) values. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2-5.
format	article
author	Emily Berger Deniz Yorukoglu Jian Peng Bonnie Berger
author_facet	Emily Berger Deniz Yorukoglu Jian Peng Bonnie Berger
author_sort	Emily Berger
title	HapTree: a novel Bayesian framework for single individual polyplotyping using NGS data.
title_short	HapTree: a novel Bayesian framework for single individual polyplotyping using NGS data.
title_full	HapTree: a novel Bayesian framework for single individual polyplotyping using NGS data.
title_fullStr	HapTree: a novel Bayesian framework for single individual polyplotyping using NGS data.
title_full_unstemmed	HapTree: a novel Bayesian framework for single individual polyplotyping using NGS data.
title_sort	haptree: a novel bayesian framework for single individual polyplotyping using ngs data.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/9e44faa798804343b74dd345c48d6308
work_keys_str_mv	AT emilyberger haptreeanovelbayesianframeworkforsingleindividualpolyplotypingusingngsdata AT denizyorukoglu haptreeanovelbayesianframeworkforsingleindividualpolyplotypingusingngsdata AT jianpeng haptreeanovelbayesianframeworkforsingleindividualpolyplotypingusingngsdata AT bonnieberger haptreeanovelbayesianframeworkforsingleindividualpolyplotypingusingngsdata
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HapTree: a novel Bayesian framework for single individual polyplotyping using NGS data.

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