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Rogue taxa phenomenon: A biological companion to simulation analysis

机译:流氓分类群现象:模拟分析的生物学伴侣

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摘要

To provide a baseline biological comparison to simulation study predictions about the frequency of rogue taxa effects, we evaluated the frequency of a rogue taxa effect using viral data sets which differed in diversity. Using a quartet-tree framework, we measured the frequency of a rogue taxa effect in three data sets of increasing genetic variability (within viral serotype, between viral serotype, and between viral family) to test whether the rogue taxa was correlated with the mean sequence diversity of the respective data sets. We found a slight increase in the percentage of rogues as nucleotide diversity increased. Even though the number of rogues increased with diversity, the distribution of the types of rogues (friendly, crazy, or evil) did not depend on the diversity and in the case of the order-level data set the net rogue effect was slightly positive. This study, assessing frequency of the rogue taxa effect using biological data, indicated that simulation studies may over-predict the prevalence of the rogue taxa effect. Further investigations are necessary to understand which types of data sets are susceptible to a negative rogue effect and thus merit the removal of taxa from large phylogenetic reconstructions.
机译:为了提供与流氓类群效应频率模拟研究预测的基线生物学比较,我们使用多样性不同的病毒数据集评估了流氓类群效应的频率。使用四重树结构,我们在三个遗传变异性不断增加的数据集中(病毒血清型内,病毒血清型之间以及病毒家族之间)测量了流氓分类群效应的频率,以测试流氓分类群是否与平均序列相关各个数据集的多样性。我们发现,随着核苷酸多样性的增加,流氓的百分比略有增加。即使流氓的数量随多样性的增加而增加,流氓类型(友好的,疯狂的或邪恶的)的分布也不取决于多样性,并且在订单级数据集的情况下,净流氓的影响是轻微的正向。这项研究使用生物学数据评估了流氓类群效应的发生频率,表明模拟研究可能会过度预测流氓类群效应的发生率。有必要进行进一步的研究,以了解哪些类型的数据集容易受到负面的恶意影响,因此值得从大型系统发育重建中移除分类单元。

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