TreeWave: command line tool for alignment-free phylogeny reconstruction based on graphical representation of DNA sequences and genomic signal processing.

IF 2.9 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS BMC Bioinformatics Pub Date : 2024-11-27 DOI:10.1186/s12859-024-05992-3
Nasma Boumajdi, Houda Bendani, Lahcen Belyamani, Azeddine Ibrahimi
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引用次数: 0

Abstract

Background: Genomic sequence similarity comparison is a crucial research area in bioinformatics. Multiple Sequence Alignment (MSA) is the basic technique used to identify regions of similarity between sequences, although MSA tools are widely used and highly accurate, they are often limited by computational complexity, and inaccuracies when handling highly divergent sequences, which leads to the development of alignment-free (AF) algorithms.

Results: This paper presents TreeWave, a novel AF approach based on frequency chaos game representation and discrete wavelet transform of sequences for phylogeny inference. We validate our method on various genomic datasets such as complete virus genome sequences, bacteria genome sequences, human mitochondrial genome sequences, and rRNA gene sequences. Compared to classical methods, our tool demonstrates a significant reduction in running time, especially when analyzing large datasets. The resulting phylogenetic trees show that TreeWave has similar classification accuracy to the classical MSA methods based on the normalized Robinson-Foulds distances and Baker's Gamma coefficients.

Conclusions: TreeWave is an open source and user-friendly command line tool for phylogeny reconstruction. It is a faster and more scalable tool that prioritizes computational efficiency while maintaining accuracy. TreeWave is freely available at https://github.com/nasmaB/TreeWave .

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TreeWave:基于 DNA 序列图形表示和基因组信号处理的无配对系统发育重建命令行工具。
背景基因组序列相似性比较是生物信息学的一个重要研究领域。多重序列比对(MSA)是用于识别序列间相似性区域的基本技术,尽管 MSA 工具被广泛使用且准确性很高,但它们往往受限于计算复杂性,以及处理高度差异序列时的不准确性,这导致了无比对算法(AF)的发展:本文介绍了 TreeWave,一种基于频率混沌博弈表示和序列离散小波变换的系统发育推断的新型 AF 方法。我们在各种基因组数据集上验证了我们的方法,如完整的病毒基因组序列、细菌基因组序列、人类线粒体基因组序列和 rRNA 基因序列。与传统方法相比,我们的工具大大缩短了运行时间,尤其是在分析大型数据集时。生成的系统发生树显示,TreeWave 与基于归一化 Robinson-Foulds 距离和 Baker's Gamma 系数的经典 MSA 方法具有相似的分类准确性:TreeWave 是一款开源且用户友好的系统发育重建命令行工具。它是一种速度更快、可扩展性更强的工具,在保证准确性的同时优先考虑计算效率。TreeWave 可在 https://github.com/nasmaB/TreeWave 免费获取。
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来源期刊
BMC Bioinformatics
BMC Bioinformatics 生物-生化研究方法
CiteScore
5.70
自引率
3.30%
发文量
506
审稿时长
4.3 months
期刊介绍: BMC Bioinformatics is an open access, peer-reviewed journal that considers articles on all aspects of the development, testing and novel application of computational and statistical methods for the modeling and analysis of all kinds of biological data, as well as other areas of computational biology. BMC Bioinformatics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.
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