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Missing Data in Phylogenetic Analysis: Reconciling Results from Simulations and Empirical Data

机译:系统发育分析中的数据丢失:模拟和经验数据的结果一致

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摘要

This paper will attempt to resolve some controversies about the effects of missing data on phylogenetic analysis. Whether missing data are generally problematic is a critical issue in modern phylogenetics, especially as wildly different amounts of molecular data become available for different taxa, ranging from entire genomes, to single genes, to none (e.g., fossils). Our perception of the impact of missing data (or lack thereof) may strongly influence which taxa and characters we include in a phylogenetic analysis (Wiens 2006) and may lead to a diversity of serious errors. For example, if we think that missing data are problematic when they are not, then we may exclude taxa and characters that would otherwise benefit our analyses, given the abundant evidence that increasing numbers of both taxa and characters can potentially improve the accuracy of phylogenetic analyses (e.g., Huelsenbeck 1995; Rannala et al. 1998; Poe 2003), where accuracy is generally defined as the similarity between the estimated tree and the correct, known phylogeny. In contrast, if missing data cells are themselves intrinsically problematic (e.g., Huelsenbeck 1991), including taxa or characters with many missing data cells may lead to inaccurate phylogenetic estimates.
机译:本文将尝试解决一些有关缺失数据对系统发育分析影响的争议。丢失的数据是否普遍存在问题是现代系统发育学中的一个关键问题,特别是当可用于不同分类单元的分子数量大不相同时,从整个基因组到单个基因,再到一个都不存在(例如化石)。我们对丢失数据(或缺少数据)的影响的感知可能会强烈影响我们在系统发育分析中包括哪些分类单元和特征(Wiens 2006),并可能导致各种严重错误。例如,如果我们认为丢失的数据在没有问题时是有问题的,那么我们可以排除可能有利于我们分析的分类和字符,因为有充分的证据表明,增加分类和字符的数量都可以潜在地改善系统发育分析的准确性(例如,Huelsenbeck 1995; Rannala等1998; Poe 2003),其中准确性通常被定义为估计树与正确的已知系统发育之间的相似性。相反,如果丢失的数据单元本身是内在的问题(例如,Huelsenbeck 1991),包括分类单元或具有很多丢失的数据单元的字符可能会导致系统发育估计不准确。

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