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DIDA: Distributed Indexing Dispatched Alignment
One essential application in bioinformatics that is affected by the high-throughput sequencing data deluge is the sequence alignment problem, where nucleotide or amino acid sequences are queried against targets to find regions of close similarity. When queries are too many and/or targets are too lar...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4414605/ https://www.ncbi.nlm.nih.gov/pubmed/25923767 http://dx.doi.org/10.1371/journal.pone.0126409 |
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author | Mohamadi, Hamid Vandervalk, Benjamin P Raymond, Anthony Jackman, Shaun D Chu, Justin Breshears, Clay P Birol, Inanc |
author_facet | Mohamadi, Hamid Vandervalk, Benjamin P Raymond, Anthony Jackman, Shaun D Chu, Justin Breshears, Clay P Birol, Inanc |
author_sort | Mohamadi, Hamid |
collection | PubMed |
description | One essential application in bioinformatics that is affected by the high-throughput sequencing data deluge is the sequence alignment problem, where nucleotide or amino acid sequences are queried against targets to find regions of close similarity. When queries are too many and/or targets are too large, the alignment process becomes computationally challenging. This is usually addressed by preprocessing techniques, where the queries and/or targets are indexed for easy access while searching for matches. When the target is static, such as in an established reference genome, the cost of indexing is amortized by reusing the generated index. However, when the targets are non-static, such as contigs in the intermediate steps of a de novo assembly process, a new index must be computed for each run. To address such scalability problems, we present DIDA, a novel framework that distributes the indexing and alignment tasks into smaller subtasks over a cluster of compute nodes. It provides a workflow beyond the common practice of embarrassingly parallel implementations. DIDA is a cost-effective, scalable and modular framework for the sequence alignment problem in terms of memory usage and runtime. It can be employed in large-scale alignments to draft genomes and intermediate stages of de novo assembly runs. The DIDA source code, sample files and user manual are available through http://www.bcgsc.ca/platform/bioinfo/software/dida. The software is released under the British Columbia Cancer Agency License (BCCA), and is free for academic use. |
format | Online Article Text |
id | pubmed-4414605 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-44146052015-05-07 DIDA: Distributed Indexing Dispatched Alignment Mohamadi, Hamid Vandervalk, Benjamin P Raymond, Anthony Jackman, Shaun D Chu, Justin Breshears, Clay P Birol, Inanc PLoS One Research Article One essential application in bioinformatics that is affected by the high-throughput sequencing data deluge is the sequence alignment problem, where nucleotide or amino acid sequences are queried against targets to find regions of close similarity. When queries are too many and/or targets are too large, the alignment process becomes computationally challenging. This is usually addressed by preprocessing techniques, where the queries and/or targets are indexed for easy access while searching for matches. When the target is static, such as in an established reference genome, the cost of indexing is amortized by reusing the generated index. However, when the targets are non-static, such as contigs in the intermediate steps of a de novo assembly process, a new index must be computed for each run. To address such scalability problems, we present DIDA, a novel framework that distributes the indexing and alignment tasks into smaller subtasks over a cluster of compute nodes. It provides a workflow beyond the common practice of embarrassingly parallel implementations. DIDA is a cost-effective, scalable and modular framework for the sequence alignment problem in terms of memory usage and runtime. It can be employed in large-scale alignments to draft genomes and intermediate stages of de novo assembly runs. The DIDA source code, sample files and user manual are available through http://www.bcgsc.ca/platform/bioinfo/software/dida. The software is released under the British Columbia Cancer Agency License (BCCA), and is free for academic use. Public Library of Science 2015-04-29 /pmc/articles/PMC4414605/ /pubmed/25923767 http://dx.doi.org/10.1371/journal.pone.0126409 Text en © 2015 Mohamadi et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Mohamadi, Hamid Vandervalk, Benjamin P Raymond, Anthony Jackman, Shaun D Chu, Justin Breshears, Clay P Birol, Inanc DIDA: Distributed Indexing Dispatched Alignment |
title | DIDA: Distributed Indexing Dispatched Alignment |
title_full | DIDA: Distributed Indexing Dispatched Alignment |
title_fullStr | DIDA: Distributed Indexing Dispatched Alignment |
title_full_unstemmed | DIDA: Distributed Indexing Dispatched Alignment |
title_short | DIDA: Distributed Indexing Dispatched Alignment |
title_sort | dida: distributed indexing dispatched alignment |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4414605/ https://www.ncbi.nlm.nih.gov/pubmed/25923767 http://dx.doi.org/10.1371/journal.pone.0126409 |
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