Zhang Chao, Nielsen Rasmus, Mirarab Siavash
Globe Institute, University of Copenhagen, Øster Voldgade 5-7, Copenhagen 1350, Denmark.
Integrative Biology Department, University of California Berkeley, 110 Sproul Hall, Berkeley, CA 94704, USA.
Mol Biol Evol. 2025 Jul 30;42(8). doi: 10.1093/molbev/msaf172.
Many algorithms are available for inferring species trees from various input types while accounting for gene tree discordance. Several quartet-based species tree inference methods, collectively known as the ASTRAL family, are based on similar ideas and are in wide use. Here, we integrate all ASTRAL-like methods into a single package called ASTER, comprising several tools, each designed for a different input type: (i) ASTRAL for single-copy gene tree topologies, (ii) weighted ASTRAL (wASTRAL) for single-copy gene tees with branch length and/or support, (iii) ASTRAL-Pro for multi-copy gene tree topologies, (iv) CASTER for multiple sequence alignments, including genome alignments, and (v) WASTER for short-reads and assembled genomes. These tools collectively enhance the scalability, accuracy, and versatility of species tree inference.
有许多算法可用于从各种输入类型推断物种树,同时考虑基因树的不一致性。几种基于四重奏的物种树推断方法,统称为ASTRAL家族,基于相似的理念并被广泛使用。在这里,我们将所有类似ASTRAL的方法整合到一个名为ASTER的单一软件包中,该软件包包含几个工具,每个工具针对不同的输入类型进行设计:(i)用于单拷贝基因树拓扑结构的ASTRAL,(ii)用于具有分支长度和/或支持度的单拷贝基因树的加权ASTRAL(wASTRAL),(iii)用于多拷贝基因树拓扑结构的ASTRAL-Pro,(iv)用于多序列比对(包括基因组比对)的CASTER,以及(v)用于短读长和组装基因组的WASTER。这些工具共同提高了物种树推断的可扩展性、准确性和通用性。