Modern Phylogenetic Comparative Methods and Their Application in Evolutionary Biology - Concepts and Practice
Modern Phylogenetic Comparative Methods and Their Application in Evolutionary Biology - Concepts and Practice
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现代系统发育比较方法及其在进化生物学中的应用 - 概念与实践
DOI：
10.1007/978-3-662-43550-2_10
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Currie T
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文献类型：
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作者：
Currie T
贝叶斯推理涉及随着我们获得更多信息而改变我们对事件发生概率的信念。这是一种明智且直观的方法，构成了我们在日常生活中做出的各种决策的基础。在本章中，我们研究如何在贝叶斯框架内执行系统发育比较方法，介绍贝叶斯统计中涉及的一些主要概念，例如先验分布和后验分布。许多生物学和进化兴趣的特征可以建模为分类的或离散分布的，在这里，我们讨论研究这些特征在系统发育树上的进化的方法。我们重点关注离散字符演化的马尔可夫链模型，以及如何使用参数估计的最大似然和马尔可夫链蒙特卡罗技术来评估这些模型。我们通过检查不同特征的相关进化来证明如何使用它来测试功能假设，并以灵长类动物和慈鲷的性选择为例进行说明。我们展示了如何确定特征进化的顺序（可能为因果假设提供更强的测试）以及如何使用贝叶斯因子评估竞争假设。这些贝叶斯方法的吸引人的特点是它们能够将物种之间系统发育关系的不确定性纳入其中，并将结果表示为概率分布而不是点估计。我们认为贝叶斯方法提供了一种更现实的评估证据的方法，并最终为调查生命多样性提供了一种在智力上更令人满意的方法。
Bayesian inference involves altering our beliefs about the probability of events occurring as we gain more information. It is a sensible and intuitive approach that forms the basis of the kinds of decisions we make in everyday life. In this chapter, we examine how phylogenetic comparative methods are performed within a Bayesian framework, introducing some of the main concepts involved in Bayesian statistics, such as prior and posterior distributions. Many traits of biological and evolutionary interest can be modelled as being categorical, or discretely distributed, and here, we discuss approaches to investigating the evolution of such characters over phylogenetic trees. We focus on Markov chain models of discrete character evolution and how these models can be assessed using maximum-likelihood and Markov Chain Monte Carlo techniques of parameter estimation. We demonstrate how this can be used to test functional hypotheses by examining the correlated evolution of different traits, illustrated with examples of sexual selection in primates and cichlid fish. We show how the order of trait evolution can be determined (potentially providing a stronger test of causal hypotheses) and how competing hypotheses can be assessed using Bayes factors. Attractive features of these Bayesian methods are their ability to incorporate uncertainty about the phylogenetic relationships between species and their representation of results as probability distributions rather than point estimates. We argue that Bayesian methods provide a more realistic way of assessing evidence and ultimately a more intellectually satisfying approach to investigating the diversity of life.