Unidad Ejecutora Lillo, Consejo Nacional de Investigaciones Científicas y Técnicas - Fundación Miguel Lillo, S. M. de Tucumán, Miguel Lillo 251, 4000, Argentina.
Unidad Ejecutora Lillo, Consejo Nacional de Investigaciones Científicas y Técnicas - Fundación Miguel Lillo, S. M. de Tucumán, Miguel Lillo 251, 4000, Argentina; Research Associate, American Museum of Natural History, New York, 200 Central Park West, 10024, USA.
Mol Phylogenet Evol. 2021 Aug;161:107086. doi: 10.1016/j.ympev.2021.107086. Epub 2021 Feb 18.
Assessing the effect of methodological decisions on the resulting hypotheses is critical in phylogenetics. Recent studies have focused on evaluating how model selection, orthology definition and confounding factors affect phylogenomic results. Here, we compare the results of three concatenated phylogenetic methods (Maximum Likelihood, ML; Bayesian Inference, BI; Maximum Parsimony, MP) in 157 empirical phylogenomic datasets. The resulting trees were very similar, with 96.7% of all nodes shared between BI and ML (90.6% for ML-MP and 89.1% for BI-MP). Differing nodes were predominantly those of lower support. The main conclusions of most of the studies agreed for the three phylogenetic methods and the discordance involved nodes considered as recalcitrant problems in systematics. The differences between methods were proportionally larger in datasets that analyze the relationships at higher taxonomic levels (particularly phyla and kingdoms), and independent of the number of characters included in the datasets. Note: a spanish version of this article is available in the Supplementary material (Supplementary material online).
评估方法决策对结果假设的影响在系统发育学中至关重要。最近的研究集中于评估模型选择、同源定义和混杂因素如何影响基因组系统发育学的结果。在这里，我们比较了 157 个经验基因组数据集的三种串联系统发育方法（最大似然法、ML；贝叶斯推断、BI；最大简约法、MP）的结果。生成的树非常相似，BI 和 ML 之间共享所有节点的 96.7%（ML-MP 为 90.6%，BI-MP 为 89.1%）。不同的节点主要是那些支持度较低的节点。对于三种系统发育方法，大多数研究的主要结论是一致的，分歧涉及到被认为是系统分类学中棘手问题的节点。方法之间的差异在分析较高分类水平（特别是门和界）关系的数据集以及与数据集所包含的字符数量无关。注意：本文的西班牙语版本可在补充材料中获得（在线补充材料）。
