Phylogenetic inference proposes an evolutionary hypothesis for a group of taxa which is usually represented as a phylogenetic tree. The use of several distinct biological evidence has shown to produce more resolved phylogenies than single evidence approaches. Currently, two conflicting paradigms are applied to combine biological evidence: taxonomic congruence (TC) and total evidence (TE). Although the literature recommends the application of these paradigms depending on the congruence of the input data, the resultant evolutionary hypotheses could vary according to the strategy used to combine the biological evidence biasing the resultant topologies of the trees. In this work, we evaluate the ability of different strategies associated with both paradigms to produce integrated evolutionary hypotheses by considering different features of the data: missing biological evidence, diversity among sequences, complexity, and congruence. Using datasets from the literature, we compare the resultant trees with reference hypotheses obtained by applying two inference criteria: maximum parsimony and likelihood. The results show that methods associated with TE paradigm are more robust compared to TC methods, obtaining trees with more similar topologies in relation to reference trees. These results are obtained regardless of (1) the features of the data, (2) the estimated evolutionary rates, and (3) the criteria used to infer the reference evolutionary hypotheses.

中文翻译：

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完全证据还是分类一致性？结合生物学证据的方法比较

系统发育推断为通常表示为系统发育树的一组分类群提出了进化假设。与单一证据方法相比，使用几种不同的生物学证据表明可以产生更多的系统发育。目前，两种相互矛盾的范式被应用于结合生物学证据：分类一致性（TC）和全证据（TE）。尽管文献建议根据输入数据的一致性应用这些范式，但最终的进化假设可能会根据用于结合生物学证据的策略而有所不同，这些生物学证据偏向于树的结果拓扑。在这项工作中，我们通过考虑数据的不同特征来评估与两种范式相关的不同策略产生综合进化假设的能力：缺少生物学证据、序列之间的多样性、复杂性和一致性。使用文献中的数据集，我们将生成的树与通过应用两个推理标准获得的参考假设进行比较：最大简约性和似然性。结果表明，与 TC 方法相比，与 TE 范式相关的方法更稳健，可以获得与参考树相关的拓扑更相似的树。无论 (1) 数据的特征，(2) 估计的进化率，以及 (3) 用于推断参考进化假设的标准，都可以获得这些结果。最大简约性和可能性。结果表明，与 TC 方法相比，与 TE 范式相关的方法更稳健，可以获得与参考树相关的拓扑更相似的树。无论 (1) 数据的特征，(2) 估计的进化率，以及 (3) 用于推断参考进化假设的标准，都可以获得这些结果。最大简约性和可能性。结果表明，与 TC 方法相比，与 TE 范式相关的方法更稳健，可以获得与参考树相关的拓扑更相似的树。无论 (1) 数据的特征，(2) 估计的进化率，以及 (3) 用于推断参考进化假设的标准，都可以获得这些结果。