The Fundamental Role of Character Coding in Bayesian Morphological Phylogenetics

生物 性格(数学) 系统发育学 进化生物学 性格演变 贝叶斯概率 人工智能 遗传学 计算机科学 数学 克莱德 基因 几何学
作者
Basanta Khakurel,Courtney Grigsby,Tyler D Tran,Juned Zariwala,Sebastian Höhna,April Wright
出处
期刊:Systematic Biology [Oxford University Press]
卷期号:73 (5): 861-871 被引量:3
标识
DOI:10.1093/sysbio/syae033
摘要

Abstract Phylogenetic trees establish a historical context for the study of organismal form and function. Most phylogenetic trees are estimated using a model of evolution. For molecular data, modeling evolution is often based on biochemical observations about changes between character states. For example, there are 4 nucleotides, and we can make assumptions about the probability of transitions between them. By contrast, for morphological characters, we may not know a priori how many characters states there are per character, as both extant sampling and the fossil record may be highly incomplete, which leads to an observer bias. For a given character, the state space may be larger than what has been observed in the sample of taxa collected by the researcher. In this case, how many evolutionary rates are needed to even describe transitions between morphological character states may not be clear, potentially leading to model misspecification. To explore the impact of this model misspecification, we simulated character data with varying numbers of character states per character. We then used the data to estimate phylogenetic trees using models of evolution with the correct number of character states and an incorrect number of character states. The results of this study indicate that this observer bias may lead to phylogenetic error, particularly in the branch lengths of trees. If the state space is wrongly assumed to be too large, then we underestimate the branch lengths, and the opposite occurs when the state space is wrongly assumed to be too small.
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