Fixed-parameter algorithms for scaffold filling
The new sequencing technologies, called next-generation sequencing, provide a huge amount of data that can be used to reconstruct genomes. However, the methods applied to reconstruct genomes often are not able to reconstruct a complete genome and provide only an incomplete information. Here we consi...
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| Vydané v: | Theoretical computer science Ročník 568; s. 72 - 83 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier B.V
01.02.2015
Elsevier |
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| ISSN: | 0304-3975, 1879-2294 |
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| Abstract | The new sequencing technologies, called next-generation sequencing, provide a huge amount of data that can be used to reconstruct genomes. However, the methods applied to reconstruct genomes often are not able to reconstruct a complete genome and provide only an incomplete information. Here we consider two combinatorial problems that aim to reconstruct complete genomes by inserting a collection of missing genes. The first problem we consider, called One-sided scaffold filling, given an incomplete genome B and a complete genome A, asks for the insertion of missing genes into an incomplete genome B with the goal of maximizing the common adjacencies between genomes B′ (resulting from the insertion of missing genes in B) and A. The second problem, called Two-sided scaffold filling, given two incomplete genomes A, B, asks for the insertion of missing genes into both genomes so that the resulting genomes A′ and B′ have the same multiset of genes and the number of common adjacencies between A′ and B′ is maximized. Both problems were proved to be NP-hard, while their parameterized complexity, when the parameter is the number of common adjacencies of the resulting genomes, was left as an open problem. In this paper, we settle this open problem by presenting fixed-parameter algorithms for One-sided scaffold filling and Two-sided scaffold filling. |
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| AbstractList | The new sequencing technologies, called next-generation sequencing, provide a huge amount of data that can be used to reconstruct genomes. However, the methods applied to reconstruct genomes often are not able to reconstruct a complete genome and provide only an incomplete information. Here we consider two combinatorial problems that aim to reconstruct complete genomes by inserting a collection of missing genes. The first problem we consider, called One-sided scaffold filling, given an incomplete genome B and a complete genome A, asks for the insertion of missing genes into an incomplete genome B with the goal of maximizing the common adjacencies between genomes B′ (resulting from the insertion of missing genes in B) and A. The second problem, called Two-sided scaffold filling, given two incomplete genomes A, B, asks for the insertion of missing genes into both genomes so that the resulting genomes A′ and B′ have the same multiset of genes and the number of common adjacencies between A′ and B′ is maximized. Both problems were proved to be NP-hard, while their parameterized complexity, when the parameter is the number of common adjacencies of the resulting genomes, was left as an open problem. In this paper, we settle this open problem by presenting fixed-parameter algorithms for One-sided scaffold filling and Two-sided scaffold filling. The new sequencing technologies, called next-generation sequencing, provide a huge amount of data that can be used to reconstruct genomes. However, the methods applied to reconstruct genomes often are not able to reconstruct a complete genome and provide only an incomplete information. Here we consider two combinatorial problems that aim to reconstruct complete genomes by inserting a collection of missing genes. The first problem we consider, called One-sided scaffold filling, given an incomplete genome B and a complete genome A, asks for the insertion of missing genes into an incomplete genome B with the goal of maximizing the common adjacencies between genomes (resulting from the insertion of missing genes in B) and A. The second problem, called Two-sided scaffold filling, given two incomplete genomes A, B, asks for the insertion of missing genes into both genomes so that the resulting genomes and have the same multiset of genes and the number of common adjacencies between and is maximized. Both problems were proved to be NP-hard, while their parameterized complexity, when the parameter is the number of common adjacencies of the resulting genomes, was left as an open problem. In this paper, we settle this open problem by presenting fixed-parameter algorithms for One-sided scaffold filling and Two-sided scaffold filling. The new sequencing technologies, called next-generation se-quencing, provide a huge amount of data that can be used to reconstruct genomes. However, the methods applied to reconstruct genomes often are not able to reconstruct a complete genome and provide only an incomplete information. Here we consider two combinatorial problems that aim to reconstruct complete genomes by inserting a collection of missing genes. The first problem we consider, called One-sided scaffold filling, given an incomplete genome B and a complete genome A, asks for the insertion of missing genes into an incomplete genome B with the goal of maximizing the common adjacencies between genomes B (resulting from the insertion of missing genes in B) and A. The second problem, called Two-sided scaffold filling, given two incomplete genomes A, B, asks for the insertion of missing genes into both genomes so that the resulting genomes A and B have the same multiset of genes and the number of common adjacencies between A and B is maximized. Both problems were proved to be NP-hard, while their parameterized complexity, when the parameter is the number of common adjacencies of the resulting genomes, was left as an open problem. In this paper, we settle this open problem by presenting fixed-parameter algorithms for One-sided scaffold filling and Two-sided scaffold filling. |
| Author | Bulteau, Laurent Dondi, Riccardo Carrieri, Anna Paola |
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| Cites_doi | 10.1109/TCBB.2013.100 10.1186/1471-2105-11-304 10.1007/978-3-642-37146-2 10.1016/j.ipl.2011.12.009 10.1016/j.ipl.2010.07.015 10.1093/bioinformatics/bti535 10.1016/j.jda.2010.09.002 10.1016/j.jcss.2010.07.003 10.1145/210332.210337 10.1126/science.1180614 10.1016/j.tcs.2014.07.011 10.1007/s00453-011-9600-8 10.1109/TCBB.2011.19 10.1137/0202019 10.1016/j.tcs.2012.08.023 10.1109/TCBB.2012.57 |
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| Keywords | Fixed-parameter algorithms Scaffold filling Genome comparison Computational biology |
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| SubjectTerms | Algorithms Bioinformatics Collection Combinatorial analysis Complexity Computational biology Computer Science Data Structures and Algorithms Fixed-parameter algorithms Gene sequencing Genes Genome comparison Genomes Insertion Scaffold filling Scaffolds |
| Title | Fixed-parameter algorithms for scaffold filling |
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