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Gene-wise resampling outperforms site-wise resampling in phylogenetic coalescence analyses

机译:基因 - 智能重采样优于系统发育聚结分析中的位点智能重新采样

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摘要

In summary ("two-step") coalescent analyses of empirical data, researchers typically apply the bootstrap to quantify branch support for clades inferred on the optimal species tree. We tested whether site-wise bootstrap analyses provide consistently more conservative support than gene-wise bootstrap analyses. We did so using data from three empirical phylogenomic studies and employed four coalescent methods (ASTRAL, MP-EST, NJst, and STAR). We demonstrate that application of site-wise bootstrapping generally resulted in gene-trees with substantial additional conflicts relative to the original data and this approach therefore cannot be relied upon to provide conservative support. Instead the site-wise bootstrap can provide high support for apparently incorrect clades. We provide a script (https://github.com/dbsloan/msc_tree_resampling) that implements gene-wise re-sampling, using either the bootstrap or the jackknife, for use with ASTRAL, MP-EST, NJst, and STAR. We demonstrate that the gene-wise bootstrap outperformed the site-wise bootstrap for the primary focal clades for all four coalescent methods that were applied to all three empirical studies. For summary coalescent analyses we suggest that gene-wise resampling support should be favored over gene + site or site-wise resampling when numerous genes are sampled because site-wise resampling causes substantially greater gene-tree-estimation error.
机译:总之(“两步”)对经验数据的束化分析,研究人员通常应用自举,以量化在最佳物种树上推断的分支机构。我们测试了站点 - 方向自举分析是否提供始终如一的更保守的支持,而不是基因 - 明智的引导分析。我们使用来自三种经验的系统核发学学研究的数据进行了处理,并采用四种聚赛方法(星形,MP-EST,NJST和Star)。我们证明,现场明智的自举的应用通常导致基因树与原始数据相对于原始数据具有实质性冲突,因此不能依赖于提供保守支持。相反,站点 - Wise Bootstrap可以为显然不正确的片状提供高支持。我们提供了一种脚本(https://github.com/dbsloan/msc_tree_resampling),它使用自举或jackknive实现基因 - 明智的重新采样,与星座,MP-EST,NJST和明星一起使用。我们证明了基因 - 明智的自举,为所有四种经验研究应用的所有四种结束方法都能表现出主要焦点片的基本方向自卷曲。对于总结结束分析,我们建议在采样许多基因时,应对基因+位点或站点 - 明智采样的基因 - 明智的重采样支持,因为存在大量基因,因为现场 - 方向重采样导致基本上更大的基因树估计误差。

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