Data from: Generalized Frequency Coding: A Method of Preparing Polymorphic Multistate Characters for Phylogenetic Analysis

A new method of coding polymorphic multistate characters for phylogenetic analysis is presented. By dividing such characters into subcharacters, their frequency distributions can be represented with discrete states. Differential weighting is employed to counter the effect of using multiple characters to represent one character. The new method, termed generalized frequency coding (GFC), is potentially superior to previously used methods in that it incorporates more information and can be applied to both qualitative and quantitative characters. The method was applied to a previously published data set that includes both types of polymorphic multistate characters, and performed well according to congruence with other studies and the g1 and nonparametric bootstrap statistics. The data set was also used to compare GFC to both gap-weighting and Manhattan distance step matrix coding. On these grounds and for philosophical reasons, GFC was found to be a better estimator of phylogeny.

本研究提出一种面向系统发育分析（phylogenetic analysis）的多态多状态性状编码新方法。通过将此类性状拆解为子性状，可将其频率分布以离散状态形式表征；本方法采用差异加权策略，以抵消因使用多个子性状代表单个原始性状所带来的偏倚效应。该新方法被命名为广义频率编码（Generalized Frequency Coding, GFC），其性能有望优于既往常用方法：不仅可整合更多信息，还可同时适配定性性状与定量性状。研究将该方法应用于一套同时涵盖两类多态多状态性状的已公开数据集，经与其他研究结果的一致性检验以及g1统计量、非参数自举（nonparametric bootstrap）统计量验证，其表现优异。该数据集还被用于对比广义频率编码与间隙加权（gap-weighting）、曼哈顿距离步长矩阵编码（Manhattan distance step matrix coding）两种方法的性能。基于上述实证结果以及理论层面的考量，广义频率编码被证实为更优的系统发育推断估计工具。