Baele Guy, Carvalho Luiz M, Brusselmans Marius, Dudas Gytis, Ji Xiang, McCrone John T, Lemey Philippe, Suchard Marc A, Rambaut Andrew
Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium.
School of Applied Mathematics, Getulio Vargas Foundation (FGV), Rio de Janeiro, Brazil.
bioRxiv. 2024 Dec 10:2024.12.08.627395. doi: 10.1101/2024.12.08.627395.
In Bayesian phylogenetic and phylodynamic studies it is common to summarise the posterior distribution of trees with a time-calibrated consensus phylogeny. While the maximum clade credibility (MCC) tree is often used for this purpose, we here show that a novel consensus 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 consensus 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 consensus tree. HIPSTR and MCC reconstructions on two Ebola virus and two SARS-CoV-2 data sets show that HIPSTR yields consensus 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 (≥ 0.50), whereas HIPSTR achieves near-perfect performance in this respect. HIPSTR also exhibits favorable computational performance over MCC in TreeAnnotator X. Comparison to the recently developed CCD0-MAP algorithm yielded mixed results, and requires more in-depth exploration in follow-up studies. TreeAnnotator X - which is part of the BEAST X (v10.5.0) software package - is available at https://github.com/beast-dev/beast-mcmc/releases.
在贝叶斯系统发育和系统动力学研究中，用时间校准的一致系统发育树来总结树的后验分布是很常见的。虽然最大分支可信度（MCC）树通常用于此目的，但我们在此表明，一种新的一致树方法——最高独立后验子树重建法（HIPSTR）——所包含的分支支持度始终高于MCC树。我们还在TreeAnnotator X的更新版本中提供了更快的计算程序，用于估计这两种一致树。TreeAnnotator X是一个开源软件程序，它总结树样本中的信息，并返回许多有用的统计数据，如一致树中各个分支的可信度。对两个埃博拉病毒和两个严重急性呼吸综合征冠状病毒2（SARS-CoV-2）数据集进行的HIPSTR和MCC重建表明，与MCC树相比，HIPSTR生成的一致树始终包含支持度更高的分支。MCC树经常未能包含几个后验概率非常高（≥0.95）的分支以及大量后验概率中等至高（≥0.50）的分支，而HIPSTR在这方面表现近乎完美。在TreeAnnotator X中，HIPSTR在计算性能上也优于MCC。与最近开发的CCD0-MAP算法的比较结果喜忧参半，需要在后续研究中进行更深入的探索。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上获取。
