Yixiao Zhai, Tong Zhou, Yanming Wei, Quan Zou, Yansu Wang
{"title":"ReAlign-N: an integrated realignment approach for multiple nucleic acid sequence alignment, combining global and local realignments.","authors":"Yixiao Zhai, Tong Zhou, Yanming Wei, Quan Zou, Yansu Wang","doi":"10.1093/nargab/lqae170","DOIUrl":null,"url":null,"abstract":"<p><p>Ensuring accurate multiple sequence alignment (MSA) is essential for comprehensive biological sequence analysis. However, the complexity of evolutionary relationships often results in variations that generic alignment tools may not adequately address. Realignment is crucial to remedy this issue. Currently, there is a lack of realignment methods tailored for nucleic acid sequences, particularly for lengthy sequences. Thus, there's an urgent need for the development of realignment methods better suited to address these challenges. This study presents ReAlign-N, a realignment method explicitly designed for multiple nucleic acid sequence alignment. ReAlign-N integrates both global and local realignment strategies for improved accuracy. In the global realignment phase, ReAlign-N incorporates K-Band and innovative memory-saving technology into the dynamic programming approach, ensuring high efficiency and minimal memory requirements for large-scale realignment tasks. The local realignment stage employs full matching and entropy scoring methods to identify low-quality regions and conducts realignment through MAFFT. Experimental results demonstrate that ReAlign-N consistently outperforms initial alignments on simulated and real datasets. Furthermore, compared to ReformAlign, the only existing multiple nucleic acid sequence realignment tool, ReAlign-N, exhibits shorter running times and occupies less memory space. The source code and test data for ReAlign-N are available on GitHub (https://github.com/malabz/ReAlign-N).</p>","PeriodicalId":33994,"journal":{"name":"NAR Genomics and Bioinformatics","volume":"6 4","pages":"lqae170"},"PeriodicalIF":4.0000,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11655299/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NAR Genomics and Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/nargab/lqae170","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Ensuring accurate multiple sequence alignment (MSA) is essential for comprehensive biological sequence analysis. However, the complexity of evolutionary relationships often results in variations that generic alignment tools may not adequately address. Realignment is crucial to remedy this issue. Currently, there is a lack of realignment methods tailored for nucleic acid sequences, particularly for lengthy sequences. Thus, there's an urgent need for the development of realignment methods better suited to address these challenges. This study presents ReAlign-N, a realignment method explicitly designed for multiple nucleic acid sequence alignment. ReAlign-N integrates both global and local realignment strategies for improved accuracy. In the global realignment phase, ReAlign-N incorporates K-Band and innovative memory-saving technology into the dynamic programming approach, ensuring high efficiency and minimal memory requirements for large-scale realignment tasks. The local realignment stage employs full matching and entropy scoring methods to identify low-quality regions and conducts realignment through MAFFT. Experimental results demonstrate that ReAlign-N consistently outperforms initial alignments on simulated and real datasets. Furthermore, compared to ReformAlign, the only existing multiple nucleic acid sequence realignment tool, ReAlign-N, exhibits shorter running times and occupies less memory space. The source code and test data for ReAlign-N are available on GitHub (https://github.com/malabz/ReAlign-N).