HIPSTR: highest independent posterior subtree reconstruction in TreeAnnotator X.

IF 5.4
Guy Baele, Luiz M Carvalho, Marius Brusselmans, Gytis Dudas, Xiang Ji, John T McCrone, Philippe Lemey, Marc A Suchard, Andrew Rambaut
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Abstract

Summary: In Bayesian phylogenetic and phylodynamic studies, it is common to summarize the posterior distribution of trees with a time-calibrated summary phylogeny. While the maximum clade credibility (MCC) tree is often used for this purpose, we here show that a novel summary tree method-the highest independent posterior subtree reconstruction, or (HIPSTR)-contains consistently higher supported clades over MCC. We also provide faster computational routines for estimating both summary trees in an updated version of TreeAnnotator X, an open-source software program that summarizes the information from a sample of trees and returns many helpful statistics such as individual clade credibilities contained in the summary tree.

Results: HIPSTR and MCC reconstructions on two Ebola virus and two SARS-CoV-2 datasets show that HIPSTR yields summary trees that consistently contain clades with higher support compared to MCC trees. The MCC trees regularly fail to include several clades with very high posterior probability (≥0.95) as well as a large number of clades with moderate to high posterior probability (≥50%), whereas HIPSTR-in particular its majority-rule extension MrHIPSTR-achieves near-perfect performance in this respect. HIPSTR and MrHIPSTR also exhibit favourable computational performance over MCC in TreeAnnotator X. Comparison to the recent CCD0-MAP algorithm yielded mixed results and requires a more in-depth investigation in follow-up studies.

Availability and implementation: TreeAnnotator X is available as part of the BEAST X (v10.5.0) software package, available at https://github.com/beast-dev/beast-mcmc/releases, and on Zenodo (DOI: https://doi.org/10.5281/zenodo.4895234).

HIPSTR:在TreeAnnotator X中最高独立后验子树重建。
摘要:在贝叶斯系统发育和系统动力学研究中,用时间校准的系统发育总结树木的后验分布是很常见的。虽然最大支系可信度(MCC)树通常用于此目的,但我们在这里展示了一种新的总结树方法-最高独立后验子树重建,或hipstr -包含比MCC更高的支持支系。我们还在更新版本的TreeAnnotator X中提供了更快的计算例程,用于估计这两种摘要树,这是一个开源软件程序,可以总结树样本中的信息并返回许多有用的统计数据,例如摘要树中包含的单个分支可信度。结果:对两个埃博拉病毒和两个SARS-CoV-2数据集的HIPSTR和MCC重建显示,与MCC树相比,HIPSTR生成的总结树始终包含具有更高支持度的进化枝。MCC树通常不包括具有非常高后验概率(≥0.95)的几个分支以及具有中高后验概率(≥50%)的大量分支,而hipstr -特别是其多数规则扩展MrHIPSTR -在这方面实现了近乎完美的性能。在TreeAnnotator x中,HIPSTR和MrHIPSTR的计算性能也优于MCC。与最近的CCD0-MAP算法比较,结果好坏参半,需要在后续研究中进行更深入的研究。可用性和实现:TreeAnnotator X是BEAST X (v10.5.0)软件包的一部分,可在https://github.com/beast-dev/beast-mcmc/releases和Zenodo (DOI: https://doi.org/10.5281/zenodo.4895234)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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