Modeling of Rate Heterogeneity in Datasets Compiled for Use With Parsimony

April M Wright, Brenen M Wynd
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Abstract

In recent years, there has been an increased interest in modeling morphological traits using Bayesian methods. Much of the work associated with modeling these characters has focused on the substitution or evolutionary model employed in the analysis. However, there are many other assumptions that researchers make in the modeling process that are consequential to estimated phylogenetic trees. One of these is how among-character rate variation (ACRV) is parameterized. In molecular data, a discretized gamma distribution is often used to allow different characters to have different rates of evolution. Morphological data are collected in ways that fundamentally differ from molecular data. In this paper, we appraise the use of standard parameters for ACRV and provide recommendations to researchers who work with morphological data in a Bayesian framework.
数据集中的速率异质性建模
近年来,人们对使用贝叶斯方法建立形态特征模型的兴趣日益浓厚。与这些特征建模相关的大部分工作都集中在分析中所采用的替代或进化模型上。然而,研究人员在建模过程中还会做出许多其他假设,这些假设对估计的系统发生树具有重要影响。其中之一就是如何对特征间速率变异(ACRV)进行参数化。在分子数据中,通常使用离散伽马分布(discretized gamma distribution)来允许不同特征具有不同的进化速率。形态数据的收集方式与分子数据有本质区别。本文评估了 ACRV 标准参数的使用情况,并为在贝叶斯框架下处理形态学数据的研究人员提供了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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