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Relaxed Neighbor Joining: A Fast Distance-Based Phylogenetic Tree Construction Method

机译:轻松邻居加入:基于距离的快速进化树构建方法

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摘要

Our ability to construct very large phylogenetic trees is becoming more important as vast amounts of sequence data are becoming readily available. Neighbor joining (NJ) is a widely used distance-based phylogenetic tree construction method that has historically been considered fast, but it is prohibitively slow for building trees from increasingly large datasets. We developed a fast variant of NJ called relaxed neighbor joining (RNJ) and performed experiments to measure the speed improvement over NJ. Since repeated runs of the RNJ algorithm generate a superset of the trees that repeated NJ runs generate, we also assessed tree quality. RNJ is dramatically faster than NJ, and the quality of resulting trees is very similar for the two algorithms. The results indicate that RNJ is a reasonable alternative to NJ and that it is especially well suited for uses that involve large numbers of taxa or highly repetitive procedures such as bootstrapping.
机译:随着大量序列数据的可得性,我们构建非常大型的系统树的能力变得越来越重要。邻居加入(NJ)是一种广泛使用的基于距离的系统树构建方法,历史上一直认为这种方法很快,但是对于从越来越大的数据集中构建树来说,它的速度太慢了。我们开发了NJ的一种快速变体,称为轻松邻居加入(RNJ),并进行了实验来测量NJ的速度提高。由于RNJ算法的重复运行生成了重复NJ运行生成的树的超集,因此我们还评估了树的质量。 RNJ比NJ快得多,并且两种算法的生成树质量非常相似。结果表明,RNJ是NJ的合理替代品,特别适用于涉及大量分类单元或高度重复程序(如引导程序)的用途。

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