The Effect of Ambiguous Data on Phylogenetic Estimates Obtained by Maximum Likelihood and Bayesian Inference
The Effect of Ambiguous Data on Phylogenetic Estimates Obtained by Maximum Likelihood and Bayesian Inference
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DOI：
10.1093/sysbio/syp017
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发表时间：
2009-02-01
影响因子：
6.5
通讯作者：
Lemmon, Emily Moriarty
中科院分区：
文献类型：
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作者：
Lemmon, Alan R.;Brown, Jeremy M.;Lemmon, Emily Moriarty
尽管越来越多的系统发育数据集不完整，但模糊数据对系统发育准确性的影响尚未得到很好的理解。我们使用4分类单元模拟来研究歧义数据（即缺失字符或空白）在最大似然（ML）和贝叶斯框架中的影响。通过以一种消除混杂因素的方式引入模糊数据，我们首次清楚地了解了模糊数据可能误导系统发育分析的机制。我们发现，在机器学习和贝叶斯框架中，位点间速率变化都可能与模糊的数据相互作用，从而产生对拓扑和分支长度的误导性估计。此外，在贝叶斯框架中，分支长度和速率异质性参数的先验会加剧模糊数据的影响，导致严重误导的二分限后验概率。模糊数据偏差的大小和方向是模糊字符的数量和分类分布、拓扑支持的强度以及模型是否正确指定的函数。本研究的结果对所有依赖于精确估计拓扑或分支长度的分析具有重要意义，包括发散时间估计、祖先状态重建、依赖树的比较方法、速率变异分析、系统发育假设检验和系统地理分析。
Although an increasing number of phylogenetic data sets are incomplete, the effect of ambiguous data on phylogenetic accuracy is not well understood. We use 4-taxon simulations to study the effects of ambiguous data (i.e., missing characters or gaps) in maximum likelihood (ML) and Bayesian frameworks. By introducing ambiguous data in a way that removes confounding factors, we provide the first clear understanding of 1 mechanism by which ambiguous data can mislead phylogenetic analyses. We find that in both ML and Bayesian frameworks, among-site rate variation can interact with ambiguous data to produce misleading estimates of topology and branch lengths. Furthermore, within a Bayesian framework, priors on branch lengths and rate heterogeneity parameters can exacerbate the effects of ambiguous data, resulting in strongly misleading bipartition posterior probabilities. The magnitude and direction of the ambiguous data bias are a function of the number and taxonomic distribution of ambiguous characters, the strength of topological support, and whether or not the model is correctly specified. The results of this study have major implications for all analyses that rely on accurate estimates of topology or branch lengths, including divergence time estimation, ancestral state reconstruction, tree-dependent comparative methods, rate variation analysis, phylogenetic hypothesis testing, and phylogeographic analysis.