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A random-permutations-based approach to fast read alignment

BACKGROUND: Read alignment is a computational bottleneck in some sequencing projects. Most of the existing software packages for read alignment are based on two algorithmic approaches: prefix-trees and hash-tables. We propose a new approach to read alignment using random permutations of strings. RES...

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Detalles Bibliográficos
Autor principal: Lederman, Roy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3622637/
https://www.ncbi.nlm.nih.gov/pubmed/23734846
http://dx.doi.org/10.1186/1471-2105-14-S5-S8
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author Lederman, Roy
author_facet Lederman, Roy
author_sort Lederman, Roy
collection PubMed
description BACKGROUND: Read alignment is a computational bottleneck in some sequencing projects. Most of the existing software packages for read alignment are based on two algorithmic approaches: prefix-trees and hash-tables. We propose a new approach to read alignment using random permutations of strings. RESULTS: We present a prototype implementation and experiments performed with simulated and real reads of human DNA. Our experiments indicate that this permutations-based prototype is several times faster than comparable programs for fast read alignment and that it aligns more reads correctly. CONCLUSIONS: This approach may lead to improved speed, sensitivity, and accuracy in read alignment. The algorithm can also be used for specialized alignment applications and it can be extended to other related problems, such as assembly. More information: http://alignment.commons.yale.edu
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spelling pubmed-36226372013-04-15 A random-permutations-based approach to fast read alignment Lederman, Roy BMC Bioinformatics Proceedings BACKGROUND: Read alignment is a computational bottleneck in some sequencing projects. Most of the existing software packages for read alignment are based on two algorithmic approaches: prefix-trees and hash-tables. We propose a new approach to read alignment using random permutations of strings. RESULTS: We present a prototype implementation and experiments performed with simulated and real reads of human DNA. Our experiments indicate that this permutations-based prototype is several times faster than comparable programs for fast read alignment and that it aligns more reads correctly. CONCLUSIONS: This approach may lead to improved speed, sensitivity, and accuracy in read alignment. The algorithm can also be used for specialized alignment applications and it can be extended to other related problems, such as assembly. More information: http://alignment.commons.yale.edu BioMed Central 2013-04-10 /pmc/articles/PMC3622637/ /pubmed/23734846 http://dx.doi.org/10.1186/1471-2105-14-S5-S8 Text en Copyright © 2013 Lederman; 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 Proceedings
Lederman, Roy
A random-permutations-based approach to fast read alignment
title A random-permutations-based approach to fast read alignment
title_full A random-permutations-based approach to fast read alignment
title_fullStr A random-permutations-based approach to fast read alignment
title_full_unstemmed A random-permutations-based approach to fast read alignment
title_short A random-permutations-based approach to fast read alignment
title_sort random-permutations-based approach to fast read alignment
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3622637/
https://www.ncbi.nlm.nih.gov/pubmed/23734846
http://dx.doi.org/10.1186/1471-2105-14-S5-S8
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