Cargando…
Fast gap-affine pairwise alignment using the wavefront algorithm
MOTIVATION: Pairwise alignment of sequences is a fundamental method in modern molecular biology, implemented within multiple bioinformatics tools and libraries. Current advances in sequencing technologies press for the development of faster pairwise alignment algorithms that can scale with increasin...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8355039/ https://www.ncbi.nlm.nih.gov/pubmed/32915952 http://dx.doi.org/10.1093/bioinformatics/btaa777 |
_version_ | 1783736701176250368 |
---|---|
author | Marco-Sola, Santiago Moure, Juan Carlos Moreto, Miquel Espinosa, Antonio |
author_facet | Marco-Sola, Santiago Moure, Juan Carlos Moreto, Miquel Espinosa, Antonio |
author_sort | Marco-Sola, Santiago |
collection | PubMed |
description | MOTIVATION: Pairwise alignment of sequences is a fundamental method in modern molecular biology, implemented within multiple bioinformatics tools and libraries. Current advances in sequencing technologies press for the development of faster pairwise alignment algorithms that can scale with increasing read lengths and production yields. RESULTS: In this article, we present the wavefront alignment algorithm (WFA), an exact gap-affine algorithm that takes advantage of homologous regions between the sequences to accelerate the alignment process. As opposed to traditional dynamic programming algorithms that run in quadratic time, the WFA runs in time O(ns), proportional to the read length n and the alignment score s, using [Formula: see text] memory. Furthermore, our algorithm exhibits simple data dependencies that can be easily vectorized, even by the automatic features of modern compilers, for different architectures, without the need to adapt the code. We evaluate the performance of our algorithm, together with other state-of-the-art implementations. As a result, we demonstrate that the WFA runs 20–300× faster than other methods aligning short Illumina-like sequences, and 10–100× faster using long noisy reads like those produced by Oxford Nanopore Technologies. AVAILABILITY AND IMPLEMENTATION: The WFA algorithm is implemented within the wavefront-aligner library, and it is publicly available at https://github.com/smarco/WFA. |
format | Online Article Text |
id | pubmed-8355039 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-83550392021-08-11 Fast gap-affine pairwise alignment using the wavefront algorithm Marco-Sola, Santiago Moure, Juan Carlos Moreto, Miquel Espinosa, Antonio Bioinformatics Original Papers MOTIVATION: Pairwise alignment of sequences is a fundamental method in modern molecular biology, implemented within multiple bioinformatics tools and libraries. Current advances in sequencing technologies press for the development of faster pairwise alignment algorithms that can scale with increasing read lengths and production yields. RESULTS: In this article, we present the wavefront alignment algorithm (WFA), an exact gap-affine algorithm that takes advantage of homologous regions between the sequences to accelerate the alignment process. As opposed to traditional dynamic programming algorithms that run in quadratic time, the WFA runs in time O(ns), proportional to the read length n and the alignment score s, using [Formula: see text] memory. Furthermore, our algorithm exhibits simple data dependencies that can be easily vectorized, even by the automatic features of modern compilers, for different architectures, without the need to adapt the code. We evaluate the performance of our algorithm, together with other state-of-the-art implementations. As a result, we demonstrate that the WFA runs 20–300× faster than other methods aligning short Illumina-like sequences, and 10–100× faster using long noisy reads like those produced by Oxford Nanopore Technologies. AVAILABILITY AND IMPLEMENTATION: The WFA algorithm is implemented within the wavefront-aligner library, and it is publicly available at https://github.com/smarco/WFA. Oxford University Press 2020-09-11 /pmc/articles/PMC8355039/ /pubmed/32915952 http://dx.doi.org/10.1093/bioinformatics/btaa777 Text en © The Author(s) 2020. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Papers Marco-Sola, Santiago Moure, Juan Carlos Moreto, Miquel Espinosa, Antonio Fast gap-affine pairwise alignment using the wavefront algorithm |
title | Fast gap-affine pairwise alignment using the wavefront algorithm |
title_full | Fast gap-affine pairwise alignment using the wavefront algorithm |
title_fullStr | Fast gap-affine pairwise alignment using the wavefront algorithm |
title_full_unstemmed | Fast gap-affine pairwise alignment using the wavefront algorithm |
title_short | Fast gap-affine pairwise alignment using the wavefront algorithm |
title_sort | fast gap-affine pairwise alignment using the wavefront algorithm |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8355039/ https://www.ncbi.nlm.nih.gov/pubmed/32915952 http://dx.doi.org/10.1093/bioinformatics/btaa777 |
work_keys_str_mv | AT marcosolasantiago fastgapaffinepairwisealignmentusingthewavefrontalgorithm AT mourejuancarlos fastgapaffinepairwisealignmentusingthewavefrontalgorithm AT moretomiquel fastgapaffinepairwisealignmentusingthewavefrontalgorithm AT espinosaantonio fastgapaffinepairwisealignmentusingthewavefrontalgorithm |