WMSA: a novel method for multiple sequence alignment of DNA sequences

Author:

Wei Yanming1ORCID,Zou Quan23ORCID,Tang Furong2,Yu Liang1ORCID

Affiliation:

1. School of Computer Science and Technology, Xidian University , Xi’an, Shaanxi 710071, China

2. Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China , Quzhou, Zhejiang 324003, China

3. Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China , Chengdu, Sichuan 610054, China

Abstract

Abstract Motivation Multiple sequence alignment (MSA) is a fundamental problem in bioinformatics. The quality of alignment will affect downstream analysis. MAFFT has adopted the Fast Fourier Transform method for searching the homologous segments and using them as anchors to divide the sequences, then making alignment only on segments, which can save time and memory without overly reducing the sequence alignment quality. MAFFT becomes slow when the dataset is large. Results We made a software, WMSA, which uses the divide-and-conquer method to split the sequences into clusters, aligns those clusters into profiles with the center star strategy and then makes a progressive profile–profile alignment. The alignment is conducted by the compiled algorithms of MAFFT, K-Band with multithread parallelism. Our method can balance time, space and quality and performs better than MAFFT in test experiments on highly conserved datasets. Availability and implementation Source code is freely available at https://github.com/malabz/WMSA/, which is implemented in C/C++ and supported on Linux, and datasets are available at https://github.com/malabz/WMSA-dataset. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Sichuan Province

Fundamental Research Funds for the Central Universities

Innovation Fund of Xidian University

China Postdoctoral Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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