TY - JOUR
T1 - Fast gap-affine pairwise alignment using the wavefront algorithm
AU - Marco-Sola, Santiago
AU - Moreto, Miquel
AU - Espinosa, Antonio
AU - Moure Lopez, Juan Carlos
N1 - © The Author(s) 2020. Published by Oxford University Press.
PY - 2020/9/11
Y1 - 2020/9/11
N2 - 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 paper, 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 O(s 2) 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 20-300x faster than other methods aligning short Illumina-like sequences, and 10-100x faster using long noisy reads like those produced by Oxford Nanopore Technologies. Availability: The WFA algorithm is implemented within the wavefront-aligner library, and it is publicly available at https://github.com/smarco/WFA Contact: [email protected]
AB - 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 paper, 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 O(s 2) 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 20-300x faster than other methods aligning short Illumina-like sequences, and 10-100x faster using long noisy reads like those produced by Oxford Nanopore Technologies. Availability: The WFA algorithm is implemented within the wavefront-aligner library, and it is publicly available at https://github.com/smarco/WFA Contact: [email protected]
UR - https://www.mendeley.com/catalogue/10a1e73b-9193-3124-ab08-5b3f4d2ba61d/
U2 - 10.1093/bioinformatics/btaa777
DO - 10.1093/bioinformatics/btaa777
M3 - Article
C2 - 32915952
SN - 1367-4803
SP - 1
EP - 8
JO - Bioinformatics
JF - Bioinformatics
ER -