Broccoli: Combining Phylogenetic and Network Analyses for Orthology Assignment
Broccoli: Combining Phylogenetic and Network Analyses for Orthology Assignment
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DOI：
10.1093/molbev/msaa159
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发表时间：
2020-11-01
影响因子：
10.7
通讯作者：
Colbourne, John K.
中科院分区：
文献类型：
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作者：
Derelle, Romain;Philippe, Herve;Colbourne, John K.
直系同源分配是比较基因组研究的关键步骤，为此开发了许多生物信息学工具。然而，所有基因聚类流程都是基于蛋白质距离分析，这受到许多人为因素的影响。在本文中，我们介绍了 Broccoli，这是一种用户友好的管道，旨在使用基于系统发育的方法高精度地推断直系同源基团和蛋白质对。简而言之，西兰花对大多数蛋白质进行超快系统发育分析，并建立直系同源关系网络。然后使用无参数机器学习算法从网络中识别直向同源组。西兰花还能够检测基因融合事件产生的嵌合蛋白，并将这些蛋白分配到相应的直系同源基团。经过两个基准数据集的测试，Broccoli 的性能优于当前的直系同源管道。此外，Broccoli 具有可扩展性，其运行时间与最近基于距离的管道类似。鉴于其高水平的性能和效率，这个新的管道代表了比较基因组研究的合适选择。西兰花可在 https://github.com/rderelle/Broccoli 上免费获取。
Orthology assignment is a key step of comparative genomic studies, for which many bioinformatic tools have been developed. However, all gene clustering pipelines are based on the analysis of protein distances, which are subject to many artifacts. In this article, we introduce Broccoli, a user-friendly pipeline designed to infer, with high precision, orthologous groups, and pairs of proteins using a phylogeny-based approach. Briefly, Broccoli performs ultrafast phy-logenetic analyses on most proteins and builds a network of orthologous relationships. Orthologous groups are then identified from the network using a parameter-free machine learning algorithm. Broccoli is also able to detect chimeric proteins resulting from gene-fusion events and to assign these proteins to the corresponding orthologous groups. Tested on two benchmark data sets, Broccoli outperforms current orthology pipelines. In addition, Broccoli is scalable, with runtimes similar to those of recent distance-based pipelines. Given its high level of performance and efficiency, this new pipeline represents a suitable choice for comparative genomic studies. Broccoli is freely available at https://github.com/rderelle/Broccoli.