Delft University of Technology, Delft Institute of Applied Mathematics, Mekelweg 4, 2628 CD, Delft, The Netherlands.
Simon Fraser University, Department of Mathematics, 8888 University Drive, Burnaby, BC V5A 1S6, Canada.
J Bioinform Comput Biol. 2021 Dec;19(6):2140012. doi: 10.1142/S0219720021400126. Epub 2021 Dec 6.
Phylogenetic networks represent evolutionary history of species and can record natural reticulate evolutionary processes such as horizontal gene transfer and gene recombination. This makes phylogenetic networks a more comprehensive representation of evolutionary history compared to phylogenetic trees. Stochastic processes for generating random trees or networks are important tools in evolutionary analysis, especially in phylogeny reconstruction where they can be utilized for validation or serve as priors for Bayesian methods. However, as more network generators are developed, there is a lack of discussion or comparison for different generators. To bridge this gap, we compare a set of phylogenetic network generators by profiling topological summary statistics of the generated networks over the number of reticulations and comparing the topological profiles.
系统发生网络代表了物种的进化历史，并且可以记录自然的网状进化过程，例如水平基因转移和基因重组。与系统发生树相比，这使得系统发生网络成为进化历史的更全面表示。生成随机树或网络的随机过程是进化分析中的重要工具，尤其是在系统发育重建中，它们可用于验证或作为贝叶斯方法的先验。但是，随着越来越多的网络生成器的开发，对于不同的生成器缺乏讨论或比较。为了弥补这一差距，我们通过比较生成网络的拓扑摘要统计信息随融合数量的变化情况并比较拓扑分布情况来比较一组系统发生网络生成器。
