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Sparse Tensor Decomposition for Haplotype Assembly of Diploids and Polyploids
BACKGROUND: Haplotype assembly is the task of reconstructing haplotypes of an individual from a mixture of sequenced chromosome fragments. Haplotype information enables studies of the effects of genetic variations on an organism’s phenotype. Most of the mathematical formulations of haplotype assembl...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5872563/ https://www.ncbi.nlm.nih.gov/pubmed/29589554 http://dx.doi.org/10.1186/s12864-018-4551-y |
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author | Hashemi, Abolfazl Zhu, Banghua Vikalo, Haris |
author_facet | Hashemi, Abolfazl Zhu, Banghua Vikalo, Haris |
author_sort | Hashemi, Abolfazl |
collection | PubMed |
description | BACKGROUND: Haplotype assembly is the task of reconstructing haplotypes of an individual from a mixture of sequenced chromosome fragments. Haplotype information enables studies of the effects of genetic variations on an organism’s phenotype. Most of the mathematical formulations of haplotype assembly are known to be NP-hard and haplotype assembly becomes even more challenging as the sequencing technology advances and the length of the paired-end reads and inserts increases. Assembly of haplotypes polyploid organisms is considerably more difficult than in the case of diploids. Hence, scalable and accurate schemes with provable performance are desired for haplotype assembly of both diploid and polyploid organisms. RESULTS: We propose a framework that formulates haplotype assembly from sequencing data as a sparse tensor decomposition. We cast the problem as that of decomposing a tensor having special structural constraints and missing a large fraction of its entries into a product of two factors, U and [Formula: see text] ; tensor [Formula: see text] reveals haplotype information while U is a sparse matrix encoding the origin of erroneous sequencing reads. An algorithm, AltHap, which reconstructs haplotypes of either diploid or polyploid organisms by iteratively solving this decomposition problem is proposed. The performance and convergence properties of AltHap are theoretically analyzed and, in doing so, guarantees on the achievable minimum error correction scores and correct phasing rate are established. The developed framework is applicable to diploid, biallelic and polyallelic polyploid species. The code for AltHap is freely available from https://github.com/realabolfazl/AltHap. CONCLUSION: AltHap was tested in a number of different scenarios and was shown to compare favorably to state-of-the-art methods in applications to haplotype assembly of diploids, and significantly outperforms existing techniques when applied to haplotype assembly of polyploids. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-018-4551-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5872563 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-58725632018-04-02 Sparse Tensor Decomposition for Haplotype Assembly of Diploids and Polyploids Hashemi, Abolfazl Zhu, Banghua Vikalo, Haris BMC Genomics Research BACKGROUND: Haplotype assembly is the task of reconstructing haplotypes of an individual from a mixture of sequenced chromosome fragments. Haplotype information enables studies of the effects of genetic variations on an organism’s phenotype. Most of the mathematical formulations of haplotype assembly are known to be NP-hard and haplotype assembly becomes even more challenging as the sequencing technology advances and the length of the paired-end reads and inserts increases. Assembly of haplotypes polyploid organisms is considerably more difficult than in the case of diploids. Hence, scalable and accurate schemes with provable performance are desired for haplotype assembly of both diploid and polyploid organisms. RESULTS: We propose a framework that formulates haplotype assembly from sequencing data as a sparse tensor decomposition. We cast the problem as that of decomposing a tensor having special structural constraints and missing a large fraction of its entries into a product of two factors, U and [Formula: see text] ; tensor [Formula: see text] reveals haplotype information while U is a sparse matrix encoding the origin of erroneous sequencing reads. An algorithm, AltHap, which reconstructs haplotypes of either diploid or polyploid organisms by iteratively solving this decomposition problem is proposed. The performance and convergence properties of AltHap are theoretically analyzed and, in doing so, guarantees on the achievable minimum error correction scores and correct phasing rate are established. The developed framework is applicable to diploid, biallelic and polyallelic polyploid species. The code for AltHap is freely available from https://github.com/realabolfazl/AltHap. CONCLUSION: AltHap was tested in a number of different scenarios and was shown to compare favorably to state-of-the-art methods in applications to haplotype assembly of diploids, and significantly outperforms existing techniques when applied to haplotype assembly of polyploids. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-018-4551-y) contains supplementary material, which is available to authorized users. BioMed Central 2018-03-21 /pmc/articles/PMC5872563/ /pubmed/29589554 http://dx.doi.org/10.1186/s12864-018-4551-y Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 | Research Hashemi, Abolfazl Zhu, Banghua Vikalo, Haris Sparse Tensor Decomposition for Haplotype Assembly of Diploids and Polyploids |
title | Sparse Tensor Decomposition for Haplotype Assembly of Diploids and Polyploids |
title_full | Sparse Tensor Decomposition for Haplotype Assembly of Diploids and Polyploids |
title_fullStr | Sparse Tensor Decomposition for Haplotype Assembly of Diploids and Polyploids |
title_full_unstemmed | Sparse Tensor Decomposition for Haplotype Assembly of Diploids and Polyploids |
title_short | Sparse Tensor Decomposition for Haplotype Assembly of Diploids and Polyploids |
title_sort | sparse tensor decomposition for haplotype assembly of diploids and polyploids |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5872563/ https://www.ncbi.nlm.nih.gov/pubmed/29589554 http://dx.doi.org/10.1186/s12864-018-4551-y |
work_keys_str_mv | AT hashemiabolfazl sparsetensordecompositionforhaplotypeassemblyofdiploidsandpolyploids AT zhubanghua sparsetensordecompositionforhaplotypeassemblyofdiploidsandpolyploids AT vikaloharis sparsetensordecompositionforhaplotypeassemblyofdiploidsandpolyploids |