1. Phylogenetic trees are currently routinely reconstructed from an alignment of character sequences (usually nucleotide sequences). Bayesian tools, such as MrBayes, RevBayes and BEAST2, have gained much popularity over the last decade, as they allow joint estimation of the posterior distribution of the phylogenetic trees and the parameters of the underlying inference model. An important ingredient of these Bayesian approaches is the species tree prior. In principle, the Bayesian framework allows for comparing different tree priors, which may elucidate the macroevolutionary processes underlying the species tree. In practice, however, only macroevolutionary models that allow for fast computation of the prior probability are used. The question is how accurate the tree estimation is when the real macroevolutionary processes are substantially different from those assumed in the tree prior.
2. Here we present pirouette, a free and open‐source r package that assesses the inference error made by Bayesian phylogenetics for a given macroevolutionary diversification model. pirouette makes use of BEAST2, but its philosophy applies to any Bayesian phylogenetic inference tool.
3. We describe pirouette’s usage providing full examples in which we interrogate a model for its power to describe another.
4. Last, we discuss the results obtained by the examples and their interpretation.

中文翻译：

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量化推理模型对贝叶斯系统发生学的影响

1. 目前，系统发育树通常是从字符序列（通常是核苷酸序列）的比对中重建的。贝叶斯工具，例如MrBayes，RevBayes和BEAST2，在过去十年中广受欢迎，因为它们允许联合估计系统树的后验分布和基础推理模型的参数。这些贝叶斯方法的重要组成部分是先验树种。原则上，贝叶斯框架允许比较不同的树先验，这可以阐明物种树下的宏观进化过程。然而，实际上，仅使用允许快速计算先验概率的宏观进化模型。
2. 在这里，我们介绍pirouette，这是一个免费的开放源代码r包，用于评估贝叶斯系统发育学对于给定的宏观进化多元化模型所做出的推断误差。回旋利用BEAST2的，但它的理念适用于任何贝叶斯推断亲缘工具。
3. 我们描述了pirouette的用法，并提供了完整的示例，在这些示例中，我们询问了一个模型来描述另一个模型的能力。
4. 最后，我们讨论通过示例获得的结果及其解释。