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Bases-dependent Rapid Phylogenetic Clustering (Bd-RPC) enables precise and efficient phylogenetic estimation in viruses

机译:碱基依赖性快速系统发育聚类 (Bd-RPC) 可实现精确高效的病毒系统发育估计

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摘要

Understanding phylogenetic relationships among species is essential for many biological studies, which call for an accurate phylogenetic tree to understand major evolutionary transitions. The phylogenetic analyses present a major challenge in estimation accuracy and computational efficiency, especially recently facing a wave of severe emerging infectious disease outbreaks. Here, we introduced a novel, efficient framework called Bases-dependent Rapid Phylogenetic Clustering (Bd-RPC) for new sample placement for viruses. In this study, a brand-new recoding method called Frequency Vector Recoding was implemented to approximate the phylogenetic distance, and the Phylogenetic Simulated Annealing Search algorithm was developed to match the recoded distance matrix with the phylogenetic tree. Meanwhile, the indel (insertion/deletion) was heuristically introduced to foreign sequence recognition for the first time. Here, we compared the Bd-RPC with the recent placement software (PAGAN2, EPA-ng, TreeBeST) and evaluated it in Alphacoronavirus, Alphaherpesvirinae, and Betacoronavirus by using Split and Robinson-Foulds distances. The comparisons showed that Bd-RPC maintained the highest precision with great efficiency, demonstrating good performance in new sample placement on all three virus genera. Finally, a user-friendly website (http://www.bd-rpc.xyz) is available for users to classify new samples instantly and facilitate exploration of the phylogenetic research in viruses, and the Bd-RPC is available on GitHub (http://github.com/Bin-Ma/bd-rpc).
机译:了解物种之间的系统发育关系对于许多生物学研究至关重要,这需要准确的系统发育树来了解主要的进化转变。系统发育分析对估计精度和计算效率提出了重大挑战,尤其是最近面临一波严重的新发传染病爆发。在这里,我们引入了一种称为碱基依赖性快速系统发育聚类 (Bd-RPC) 的新型、高效的框架,用于病毒的新样本放置。在这项研究中,实现了一种称为频率向量重新编码的全新重新编码方法来近似系统发育距离,并开发了系统发育模拟退火搜索算法来将重新编码的距离矩阵与系统发育树相匹配。同时,插入缺失 (插入/缺失) 首次被启发式地引入外来序列识别。在这里,我们将 Bd-RPC 与最近的放置软件 (PAGAN2、EPA-ng、TreeBeST) 进行了比较,并使用 Split 和 Robinson-Foulds 距离在 Alphacoronavirus、Alphaherpesvirinae 和 Beta冠状病毒中对其进行了评估。比较表明,Bd-RPC 保持了最高的精度和很高的效率,在所有三个病毒属的新样品放置中表现出良好的性能。最后,一个用户友好的网站 (http://www.bd-rpc.xyz) 可供用户立即对新样本进行分类并促进对病毒系统发育研究的探索,而 Bd-RPC 可在 GitHub (http://github.com/Bin-Ma/bd-rpc) 上获得。

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