Virus and Prion Research Unit, National Animal Disease Center, USDA-ARS, Ames, IA 50010, USA.
Department of Computer Science, Iowa State University, Ames, IA 50011, USA.
Bioinformatics. 2021 Nov 18;37(22):4064-4074. doi: 10.1093/bioinformatics/btab414.
The classic multispecies coalescent (MSC) model provides the means for theoretical justification of incomplete lineage sorting-aware species tree inference methods. This has motivated an extensive body of work on phylogenetic methods that are statistically consistent under MSC. One such particularly popular method is ASTRAL, a quartet-based species tree inference method. Novel studies suggest that ASTRAL also performs well when given multi-locus gene trees in simulation studies. Further, Legried et al. recently demonstrated that ASTRAL is statistically consistent under the gene duplication and loss model (GDL). GDL is prevalent in evolutionary histories and is the first core process in the powerful duplication-loss-coalescence evolutionary model (DLCoal) by Rasmussen and Kellis.
In this work, we prove that ASTRAL is statistically consistent under the general DLCoal model. Therefore, our result supports the empirical evidence from the simulation-based studies. More broadly, we prove that the quartet-based inference approach is statistically consistent under DLCoal.
Supplementary data are available at Bioinformatics online.
经典的多物种合并(MSC)模型为不完全谱系分选感知的种系发生树推断方法提供了理论依据。这激发了大量基于 MSC 的系统发育方法的研究,其中一种特别受欢迎的方法是基于四分体的种系发生树推断方法 ASTRAL。新的研究表明,在模拟研究中,当给定多基因树时,ASTRAL 也能很好地工作。此外,Legried 等人最近证明,在基因复制和丢失模型(GDL)下,ASTRAL 是统计一致的。GDL 在进化历史中很普遍,是由 Rasmussen 和 Kellis 提出的强大的复制-丢失-合并进化模型(DLCoal)的第一个核心过程。
在这项工作中,我们证明了 ASTRAL 在一般的 DLCoal 模型下是统计一致的。因此,我们的结果支持了基于模拟研究的经验证据。更广泛地说,我们证明了基于四分体的推断方法在 DLCoal 下是统计一致的。
补充数据可在“Bioinformatics”在线获取。