Efficient assembly consensus algorithms for divergent contig sets

Assembly is a fundamental task in genome sequencing, and many assemblers have been made available in the last decade. Because of the wide range of possible choices, it can be hard to determine which tool or parameter to use for a specific genome sequencing project. In this paper, we propose a consen...

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Published in:	Computational biology and chemistry Vol. 93; p. 107516
Main Authors:	Chateau, Annie, Davot, Tom, Lafond, Manuel
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.08.2021 Elsevier
Subjects:	B.2.4.a Algorithms Bioinformatics Computational Complexity Computer Science F.2 Analysis of algorithms and problem complexity L.3.0.j. Molecular biology L.3.0.j. Molecular biology F.2 Analysis of algorithms and problem complexity B.2.4.a Algorithms F.2 Analysis of Algorithms and Problem Complexity L.3.0.j. Molecular biology 3
ISSN:	1476-9271, 1476-928X, 1476-928X
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Abstract	Assembly is a fundamental task in genome sequencing, and many assemblers have been made available in the last decade. Because of the wide range of possible choices, it can be hard to determine which tool or parameter to use for a specific genome sequencing project. In this paper, we propose a consensus approach that takes the best parts of several contigs datasets produced by different methods, and combines them into a better assembly. This amounts to orienting and ordering sets of contigs, which can be viewed as an optimization problem where the aim is to find an alignment of two fragmented strings that maximizes an arbitrary scoring function between matched characters. In this work, we investigate the computational complexity of this problem. We first show that it is NP-hard, even in an alphabet with only two symbols and with all scores being either 0 or 1. On the positive side, we propose an efficient, quadratic time algorithm that achieves approximation factor 3.
AbstractList	Assembly is a fundamental task in genome sequencing, and many assemblers have been made available in the last decade. Because of the wide range of possible choices, it can be hard to determine which tool or parameter to use for a specific genome sequencing project. In this paper, we propose a consensus approach that takes the best parts of several contigs datasets produced by different methods, and combines them into a better assembly. This amounts to orienting and ordering sets of contigs, which can be viewed as an optimization problem where the aim is to find an alignment of two fragmented strings that maximizes an arbitrary scoring function between matched characters. In this work, we investigate the computational complexity of this problem. We first show that it is NP-hard, even in an alphabet with only two symbols and with all scores being either 0 or 1. On the positive side, we propose an efficient, quadratic time algorithm that achieves approximation factor 3. Assembly is a fundamental task in genome sequencing, and many assemblers have been made available in the last decade. Because of the wide range of possible choices, it can be hard to determine which tool or parameter to use for a specific genome sequencing project. In this paper, we propose a consensus approach that takes the best parts of several contigs datasets produced by different methods, and combines them into a better assembly. This amounts to orienting and ordering sets of contigs, which can be viewed as an optimization problem where the aim is to find an alignment of two fragmented strings that maximizes an arbitrary scoring function between matched characters. In this work, we investigate the computational complexity of this problem. We first show that it is NP-hard, even in an alphabet with only two symbols and with all scores being either 0 or 1. On the positive side, we propose an efficient, quadratic time algorithm that achieves approximation factor 3.Assembly is a fundamental task in genome sequencing, and many assemblers have been made available in the last decade. Because of the wide range of possible choices, it can be hard to determine which tool or parameter to use for a specific genome sequencing project. In this paper, we propose a consensus approach that takes the best parts of several contigs datasets produced by different methods, and combines them into a better assembly. This amounts to orienting and ordering sets of contigs, which can be viewed as an optimization problem where the aim is to find an alignment of two fragmented strings that maximizes an arbitrary scoring function between matched characters. In this work, we investigate the computational complexity of this problem. We first show that it is NP-hard, even in an alphabet with only two symbols and with all scores being either 0 or 1. On the positive side, we propose an efficient, quadratic time algorithm that achieves approximation factor 3.
ArticleNumber	107516
Author	Davot, Tom Chateau, Annie Lafond, Manuel
Author_xml	– sequence: 1 givenname: Annie surname: Chateau fullname: Chateau, Annie email: chateau@lirmm.fr organization: LIRMM – CNRS UMR 5506 Montpellier, France – sequence: 2 givenname: Tom orcidid: 0000-0003-4203-5140 surname: Davot fullname: Davot, Tom email: davot@lirmm.fr organization: LIRMM – CNRS UMR 5506 Montpellier, France – sequence: 3 givenname: Manuel orcidid: 0000-0002-5305-7372 surname: Lafond fullname: Lafond, Manuel email: manuel.lafond@USherbrooke.ca organization: Université de Sherbrooke, Canada
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Cites_doi	10.1093/bioinformatics/bts174 10.1371/journal.pone.0060843 10.1101/gr.089532.108 10.1186/1471-2105-14-S15-S16 10.1101/gr.126953.111 10.1101/gr.223057.117 10.3389/fgene.2017.00023 10.1101/gr.213959.116 10.1016/S0166-218X(02)00289-5 10.1101/gr.072033.107 10.1093/bioinformatics/btv688 10.1186/gb-2012-13-12-r122 10.1371/journal.pone.0011147 10.1002/cpmb.59 10.1093/bioinformatics/btr588 10.1093/bioinformatics/btm542 10.1038/s41587-019-0072-8 10.1137/0204035 10.1016/j.ymeth.2016.02.020 10.1186/1471-2105-14-S7-S6 10.1093/bioinformatics/btl158 10.1145/2151171.2151177 10.1101/gr.074492.107 10.1101/gr.091777.109 10.1145/1041680.1041683 10.1145/28869.28874 10.1016/j.mimet.2018.06.007 10.2174/1568026613666131204110628 10.1093/nar/gks678
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Title	Efficient assembly consensus algorithms for divergent contig sets
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