Genomic data have had a profound impact on nearly every biological discipline. In systematics and phylogenetics, the thousands of loci that are now being sequenced can be analyzed under the multispecies coalescent model (MSC) to explicitly account for gene tree discordance due to incomplete lineage sorting (ILS). However, the MSC assumes no gene flow post divergence, calling for additional methods that can accommodate this limitation. Explicit phylogenetic network methods have emerged, which can simultaneously account for ILS and gene flow by representing evolutionary history as a directed acyclic graph. In this point-of-view we highlight some of the strengths and limitations of phylogenetic networks and argue that tree-based inference should not be blindly abandoned in favor of networks simply because they represent more parameter rich models. Attention should be given to model selection of reticulation complexity, and the most robust conclusions regarding evolutionary history are likely obtained when combining tree- and network-based inference.

中文翻译：

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系统发育树和网络可以作为分析基因组数据的强大而互补的方法

基因组数据对几乎所有生物学科都产生了深远的影响。在系统学和系统发育学中，现在正在测序的数千个基因座可以在多物种聚结模型 (MSC) 下进行分析，以明确解释由于谱系分类 (ILS) 不完全导致的基因树不一致。然而，MSC 假设在发散后没有基因流动，需要其他方法来适应这种限制。显式系统发育网络方法已经出现，它可以通过将进化历史表示为有向无环图来同时解释 ILS 和基因流。在这个观点中，我们强调了系统发育网络的一些优势和局限性，并认为不应仅仅因为网络代表更多参数丰富的模型就盲目地放弃基于树的推理而支持网络。