Biodiversity and Biocomplexity Unit, Okinawa Institute of Science and Technology Graduate University, Onna, Japan.
Cognitive Neurorobotics Research Unit, Okinawa Institute of Science and Technology Graduate University, Onna, Japan.
Mol Ecol Resour. 2020 May;20(3). doi: 10.1111/1755-0998.13149. Epub 2020 Mar 24.
Multilocus genomic data sets can be used to infer a rich set of information about the evolutionary history of a lineage, including gene trees, species trees, and phylogenetic networks. However, user-friendly tools to run such integrated analyses are lacking, and workflows often require tedious reformatting and handling time to shepherd data through a series of individual programs. Here, we present a tool written in Python-TREEasy-that performs automated sequence alignment (with MAFFT), gene tree inference (with IQ-Tree), species inference from concatenated data (with IQ-Tree and RaxML-NG), species tree inference from gene trees (with ASTRAL, MP-EST, and STELLS2), and phylogenetic network inference (with SNaQ and PhyloNet). The tool only requires FASTA files and nine parameters as inputs. The tool can be run as command line or through a Graphical User Interface (GUI). As examples, we reproduced a recent analysis of staghorn coral evolution, and performed a new analysis on the evolution of the "WGD clade" of yeast. The latter revealed novel patterns that were not identified by previous analyses. TREEasy represents a reliable and simple tool to accelerate research in systematic biology (https://github.com/MaoYafei/TREEasy).
多基因座基因组数据集可用于推断谱系进化历史的丰富信息，包括基因树、物种树和系统发育网络。然而，缺乏用户友好的工具来运行此类综合分析，工作流程通常需要繁琐的重新格式化和处理时间，以便将数据引导通过一系列单独的程序。在这里，我们介绍了一个用 Python 编写的工具-TREEasy-它可以自动执行序列比对（使用 MAFFT）、基因树推断（使用 IQ-Tree）、从连接数据推断物种（使用 IQ-Tree 和 RaxML-NG）、从基因树推断物种树（使用 ASTRAL、MP-EST 和 STELLS2）和系统发育网络推断（使用 SNaQ 和 PhyloNet）。该工具仅需要 FASTA 文件和九个参数作为输入。该工具可以通过命令行或图形用户界面（GUI）运行。作为示例，我们重现了最近对鹿角珊瑚进化的分析，并对酵母的“WGD 分支”进化进行了新的分析。后者揭示了以前的分析没有识别出的新模式。TREEasy 是一个可靠且简单的工具，可以加速系统生物学的研究（https://github.com/MaoYafei/TREEasy）。
