HAlign 4: a new strategy for rapidly aligning millions of sequences.

Tong Zhou, Pinglu Zhang, Quan Zou, Wu Han
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Abstract

Motivation: HAlign is a high-performance multiple sequence alignment software based on the star alignment strategy, which is the preferred choice for rapidly aligning large numbers of sequences. HAlign3, implemented in Java, is the latest version capable of aligning an ultra-large number of similar DNA/RNA sequences. However, HAlign3 still struggles with long sequences and extremely large numbers of sequences.

Results: To address this issue, we have implemented HAlign4 in C++. In this version, we replaced the original suffix tree with Burrows-Wheeler Transform and introduced the wavefront alignment algorithm to further optimize both time and memory efficiency. Experiments show that HAlign4 significantly outperforms HAlign3 in runtime and memory usage in both single-threaded and multi-threaded configurations, while maintains high alignment accuracy comparable to MAFFT. HAlign4 can complete the alignment of 10 million coronavirus disease 2019 (COVID-19) sequences in about 12 min and 300 GB of memory using 96 threads, demonstrating its efficiency and practicality for large-scale alignment on standard workstations.

Availability and implementation: Source code is available at https://github.com/malabz/HAlign-4, dataset is available at https://zenodo.org/records/13934503.

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HAlign 4:一种快速对齐数百万序列的新策略。
动机:HAlign是一款基于星型比对策略的高性能多序列比对软件,是快速比对大量序列的首选。HAlign3是用Java实现的,是最新版本,能够对大量相似的DNA/RNA序列进行比对。然而,HAlign3仍然在与长序列和大量序列作斗争。结果:为了解决这个问题,我们在c++中实现了HAlign4。在这个版本中,我们用Burrows-Wheeler Transform (BWT)代替了原来的后缀树,并引入了波前对齐算法,进一步优化了时间和内存效率。实验表明,在单线程和多线程配置下,HAlign4在运行时和内存使用方面都明显优于HAlign3,同时保持与MAFFT相当的高对齐精度。HAlign4可以在约12分钟内完成1000万个COVID-19序列的比对,使用96个线程,占用300GB内存,证明了其在标准工作站上进行大规模比对的效率和实用性。可用性:源代码可在https://github.com/malabz/HAlign-4上获得,数据集可在https://zenodo.org/records/13934503.Supplementary上获得信息:补充数据可在Bioinformatics在线上获得。
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