Phylo-rs: an extensible phylogenetic analysis library in rust.

IF 3.3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Sriram Vijendran, Tavis Anderson, Alexey Markin, Oliver Eulenstein
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引用次数: 0

Abstract

Background: The advent of next-generation and long-read sequencing technologies has provided an ever-increasing wealth of phylogenetic data that require specially designed algorithms to decipher the underlying evolutionary relationships. As large-scale data become increasingly accessible, there is a concomitant need for efficient computational libraries that facilitate the development and dissemination of specialized algorithms for phylogenetic comparative biology.

Results: We introduce Phylo-rs: a fast, extensible, general-purpose library for phylogenetic analysis and inference written in the Rust programming language. Phylo-rs leverages a combination of speed, memory-safety, and native WebAssembly support offered by Rust to provide a robust set of memory-efficient data structures and elementary phylogenetic algorithms. Phylo-rs focuses on the efficient and convenient deployment of software aimed at large-scale phylogenetic analysis and inference. Scalability analysis against popular libraries shows that Phylo-rs performs comparably or better on key algorithms. We utilized it to assess the phylogenetic diversity of influenza A virus in swine, identifying virus groups that are undergoing evolutionary expansion that could be targeted for control through multivalent vaccines. Additionally, we used Phylo-rs to enhance phylogenetic inference by visualizing tree space from Markov chain Monte Carlo (MCMC) Bayesian analysis, efficiently computing approximately five billion tree pair distances to evaluate convergence and select MCMC runs for genomic epidemiology.

Conclusion: Phylo-rs enables the design and implementation of cutting-edge software for phylogenetic analysis, thereby facilitating the application and dissemination of theoretical advancements in biology. Phylo-rs is available under an open-source license on GitHub at https://github.com/sriram98v/phylo-rs , with documentation available at https://docs.rs/phylo/latest/phylo/ .

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Phylo-rs:一个可扩展的rust系统发育分析库。
背景:下一代和长读测序技术的出现提供了越来越丰富的系统发育数据,需要专门设计的算法来破译潜在的进化关系。随着大规模数据变得越来越容易获取,对高效计算库的需求也随之产生,以促进系统发育比较生物学专门算法的发展和传播。结果:我们介绍了Phylo-rs:一个快速,可扩展,通用的库,用于系统发育分析和推理,用Rust编程语言编写。Phylo-rs利用了Rust提供的速度、内存安全性和本地WebAssembly支持的组合,提供了一组健壮的内存高效数据结构和基本的系统发育算法。Phylo-rs专注于高效和方便的软件部署,旨在大规模的系统发育分析和推理。针对流行库的可伸缩性分析表明,Phylo-rs在关键算法上的性能相当甚至更好。我们利用它来评估猪甲型流感病毒的系统发育多样性,确定正在经历进化扩展的病毒群,可以通过多价疫苗进行控制。此外,我们使用Phylo-rs通过马尔可夫链蒙特卡罗(MCMC)贝叶斯分析的可视化树空间来增强系统发育推断,有效地计算了大约50亿个树对距离,以评估收敛性并选择MCMC运行基因组流行病学。结论:Phylo-rs能够设计和实现尖端的系统发育分析软件,从而促进生物学理论进展的应用和传播。Phylo-rs在GitHub上的开源许可下可在https://github.com/sriram98v/phylo-rs上获得,文档可在https://docs.rs/phylo/latest/phylo/上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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