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Efficient parallel and out of core algorithms for constructing large bi-directed de Bruijn graphs

BACKGROUND: Assembling genomic sequences from a set of overlapping reads is one of the most fundamental problems in computational biology. Algorithms addressing the assembly problem fall into two broad categories - based on the data structures which they employ. The first class uses an overlap/strin...

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Autores principales: Kundeti, Vamsi K, Rajasekaran, Sanguthevar, Dinh, Hieu, Vaughn, Matthew, Thapar, Vishal
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2996408/
https://www.ncbi.nlm.nih.gov/pubmed/21078174
http://dx.doi.org/10.1186/1471-2105-11-560
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author Kundeti, Vamsi K
Rajasekaran, Sanguthevar
Dinh, Hieu
Vaughn, Matthew
Thapar, Vishal
author_facet Kundeti, Vamsi K
Rajasekaran, Sanguthevar
Dinh, Hieu
Vaughn, Matthew
Thapar, Vishal
author_sort Kundeti, Vamsi K
collection PubMed
description BACKGROUND: Assembling genomic sequences from a set of overlapping reads is one of the most fundamental problems in computational biology. Algorithms addressing the assembly problem fall into two broad categories - based on the data structures which they employ. The first class uses an overlap/string graph and the second type uses a de Bruijn graph. However with the recent advances in short read sequencing technology, de Bruijn graph based algorithms seem to play a vital role in practice. Efficient algorithms for building these massive de Bruijn graphs are very essential in large sequencing projects based on short reads. In an earlier work, an O(n/p) time parallel algorithm has been given for this problem. Here n is the size of the input and p is the number of processors. This algorithm enumerates all possible bi-directed edges which can overlap with a node and ends up generating Θ(nΣ) messages (Σ being the size of the alphabet). RESULTS: In this paper we present a Θ(n/p) time parallel algorithm with a communication complexity that is equal to that of parallel sorting and is not sensitive to Σ. The generality of our algorithm makes it very easy to extend it even to the out-of-core model and in this case it has an optimal I/O complexity of [Formula: see text] (M being the main memory size and B being the size of the disk block). We demonstrate the scalability of our parallel algorithm on a SGI/Altix computer. A comparison of our algorithm with the previous approaches reveals that our algorithm is faster - both asymptotically and practically. We demonstrate the scalability of our sequential out-of-core algorithm by comparing it with the algorithm used by VELVET to build the bi-directed de Bruijn graph. Our experiments reveal that our algorithm can build the graph with a constant amount of memory, which clearly outperforms VELVET. We also provide efficient algorithms for the bi-directed chain compaction problem. CONCLUSIONS: The bi-directed de Bruijn graph is a fundamental data structure for any sequence assembly program based on Eulerian approach. Our algorithms for constructing Bi-directed de Bruijn graphs are efficient in parallel and out of core settings. These algorithms can be used in building large scale bi-directed de Bruijn graphs. Furthermore, our algorithms do not employ any all-to-all communications in a parallel setting and perform better than the prior algorithms. Finally our out-of-core algorithm is extremely memory efficient and can replace the existing graph construction algorithm in VELVET.
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spelling pubmed-29964082011-01-05 Efficient parallel and out of core algorithms for constructing large bi-directed de Bruijn graphs Kundeti, Vamsi K Rajasekaran, Sanguthevar Dinh, Hieu Vaughn, Matthew Thapar, Vishal BMC Bioinformatics Research Article BACKGROUND: Assembling genomic sequences from a set of overlapping reads is one of the most fundamental problems in computational biology. Algorithms addressing the assembly problem fall into two broad categories - based on the data structures which they employ. The first class uses an overlap/string graph and the second type uses a de Bruijn graph. However with the recent advances in short read sequencing technology, de Bruijn graph based algorithms seem to play a vital role in practice. Efficient algorithms for building these massive de Bruijn graphs are very essential in large sequencing projects based on short reads. In an earlier work, an O(n/p) time parallel algorithm has been given for this problem. Here n is the size of the input and p is the number of processors. This algorithm enumerates all possible bi-directed edges which can overlap with a node and ends up generating Θ(nΣ) messages (Σ being the size of the alphabet). RESULTS: In this paper we present a Θ(n/p) time parallel algorithm with a communication complexity that is equal to that of parallel sorting and is not sensitive to Σ. The generality of our algorithm makes it very easy to extend it even to the out-of-core model and in this case it has an optimal I/O complexity of [Formula: see text] (M being the main memory size and B being the size of the disk block). We demonstrate the scalability of our parallel algorithm on a SGI/Altix computer. A comparison of our algorithm with the previous approaches reveals that our algorithm is faster - both asymptotically and practically. We demonstrate the scalability of our sequential out-of-core algorithm by comparing it with the algorithm used by VELVET to build the bi-directed de Bruijn graph. Our experiments reveal that our algorithm can build the graph with a constant amount of memory, which clearly outperforms VELVET. We also provide efficient algorithms for the bi-directed chain compaction problem. CONCLUSIONS: The bi-directed de Bruijn graph is a fundamental data structure for any sequence assembly program based on Eulerian approach. Our algorithms for constructing Bi-directed de Bruijn graphs are efficient in parallel and out of core settings. These algorithms can be used in building large scale bi-directed de Bruijn graphs. Furthermore, our algorithms do not employ any all-to-all communications in a parallel setting and perform better than the prior algorithms. Finally our out-of-core algorithm is extremely memory efficient and can replace the existing graph construction algorithm in VELVET. BioMed Central 2010-11-15 /pmc/articles/PMC2996408/ /pubmed/21078174 http://dx.doi.org/10.1186/1471-2105-11-560 Text en Copyright ©2010 Kundeti et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Kundeti, Vamsi K
Rajasekaran, Sanguthevar
Dinh, Hieu
Vaughn, Matthew
Thapar, Vishal
Efficient parallel and out of core algorithms for constructing large bi-directed de Bruijn graphs
title Efficient parallel and out of core algorithms for constructing large bi-directed de Bruijn graphs
title_full Efficient parallel and out of core algorithms for constructing large bi-directed de Bruijn graphs
title_fullStr Efficient parallel and out of core algorithms for constructing large bi-directed de Bruijn graphs
title_full_unstemmed Efficient parallel and out of core algorithms for constructing large bi-directed de Bruijn graphs
title_short Efficient parallel and out of core algorithms for constructing large bi-directed de Bruijn graphs
title_sort efficient parallel and out of core algorithms for constructing large bi-directed de bruijn graphs
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2996408/
https://www.ncbi.nlm.nih.gov/pubmed/21078174
http://dx.doi.org/10.1186/1471-2105-11-560
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