Concatabominations: identifying unstable taxa in morphological phylogenetics using a heuristic extension to safe taxonomic reduction.
Concatabominations: identifying unstable taxa in morphological phylogenetics using a heuristic extension to safe taxonomic reduction.
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DOI：
10.1093/sysbio/syu066
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发表时间：
2015-01
影响因子：
6.5
通讯作者：
Wilkinson M
中科院分区：
文献类型：
--
作者：
Siu-Ting K;Pisani D;Creevey CJ;Wilkinson M
由于各种原因，一些系统发育数据集充满了缺失的条目。对大量缺失数据的态度，特别是对其可能误导或混淆系统发育推断的关注，各不相同。因此，目前存在关于缺失条目对系统发育推断准确性影响的争论（Wiens 2006； Lemmon等人2009；Philippe等人2011；Wiens和Morrill 2011； Roure等人2013）。也许较少争议的是，由于有限的数据和大量的缺失数据，单个分类群有时可能相对不稳定（例如，Wilkinson 1996; Sanderson and Shaffer 2002; Wiens 2003; Wilkinson 2003）。Wilkinson（1995）开发了一种诊断分类单元不稳定性的方法，这种方法是由于先验数据缺失而被称为安全分类还原（STR）。STR允许识别“流氓”分类群，这些分类群可以安全地从数据集中删除，因为它们的删除不会影响根据简约标准推断出的剩余分类群之间的相互关系。这种删除的潜在好处是减少了最优树的数量和运行时间，并更好地解决了共识摘要。STR已经得到了相当广泛的应用，主要是在古生物学家面对相对不完整的化石分类群时（参见Anquetin 2012； Graf 2012; McDonald 2012；一些最近的例子），以及在用简约的矩阵表示方法构建超树的背景下（Baum 1992; Ragan 1992）（例如Cardillo et al. 2004）。尽管如此，STR并不总是像人们希望的那样有效（例如，Mannion et al. 2013）。在这里，我们提出了一种简单的启发式方法来识别潜在的不稳定分类群，这种方法在STR不能成功改善由丢失数据引起的所有问题的情况下可能很有用。我们通过应用Gauthier（1986）的蜥脚类数据来说明该方法，该数据先前用于说明STR，因此特别适合于证明新方法的能力，而不仅仅是STR。
For a variety of reasons, some phylogenetic data sets are replete with missing entries. Attitudes toward abundant missing data, specifically concerns over its potential to mislead or confound phylogenetic inferences, are varied. Thus, there is a current debate on the impact of missing entries upon the accuracy of phylogenetic inferences (Wiens 2006; Lemmon et al. 2009; Philippe et al. 2011; Wiens and Morrill 2011; Roure et al. 2013). Perhaps less controversial is that individual taxa may sometimes be relatively phylogenetically unstable by virtue of limited data and extensive missing data (eg, Wilkinson 1996; Sanderson and Shaffer 2002; Wiens 2003; Wilkinson 2003). Wilkinson (1995) developed an approach for diagnosing taxon instability due to missing data a priori termed safe taxonomic reduction (STR). STR allows the identification of “rogue” taxa that can be removed from a data set safe in the knowledge that their removal will not impact upon the interrelationships that will be inferred among the remaining taxa under the parsimony criterion. The potential benefits of such deletion are reductions in numbers of optimal trees and run times and better resolved consensus summaries. STR has been fairly widely used, mainly by paleontologists confronted with relatively incomplete fossil taxa (see Anquetin 2012; Graf 2012; McDonald 2012; for some recent examples), and also in the context of the matrix representation with parsimony (Baum 1992; Ragan 1992) approach to supertree construction (eg, Cardillo et al. 2004). Nonetheless STR is not always as effective as one might hope (eg, Mannion et al. 2013). Here, we present a simple heuristic method for identifying potentially unstable taxa that may be useful in cases where STR does not succeed in ameliorating all the problems caused by missing data. We illustrate the approach through application to the saurischian data of Gauthier (1986), which was previously used to illustrate STR and thus is particularly appropriate for demonstrating the ability of the new method to achieve more than STR alone.
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影响因子：
4.1
作者：
Ragan, Mark A.
通讯作者：
Ragan, Mark A.
影响因子：
6.5
作者：
Lemmon, Alan R.;Brown, Jeremy M.;Lemmon, Emily Moriarty
通讯作者：
Lemmon, Emily Moriarty
影响因子：
3.4
作者：
BAUM, BR
通讯作者：
BAUM, BR
影响因子：
10.7
作者：
Roure, Beatrice;Baurain, Denis;Philippe, Herve
通讯作者：
Philippe, Herve
影响因子：
2.6
作者：
Anquetin, Jeremy
通讯作者：
Anquetin, Jeremy