Mol Biol Evol. 2010 Dec;27(12):2674-7. doi: 10.1093/molbev/msq163. Epub 2010 Jun 28.
Phylogenetic tree-search is a major aspect of many evolutionary studies. Several tree rearrangement algorithms are available for tree-search, but it is hard to draw general conclusions about their relative performance because many effects are data set specific and can be highly dependent on individual implementations (e.g., RAxML or phyml). Using only the structure of the rearrangements proposed by the Nearest Neighbor Interchange (NNI) algorithm, we show tree-search can prematurely terminate if it encounters multifurcating trees. We validate the relevance of this result by demonstrating that in real data the majority of possible bifurcating trees potentially encountered during tree-search are actually multifurcations, which suggests NNI would be expected to perform poorly. We also show that the star-decomposition algorithm is a special case of two other popular tree-search algorithms, subtree pruning and regrafting (SPR) and tree bisection and reconnection (TBR), which means that these two algorithms can efficiently escape when they encounter multifurcations. We caution against the use of the NNI algorithm and for most applications we recommend the use of more robust tree-search algorithms, such as SPR and TBR.
系统发育树搜索是许多进化研究的主要方面。有几种树重排算法可用于树搜索,但很难得出关于它们相对性能的一般结论,因为许多影响是数据集特定的,并且可能高度依赖于各个实现(例如,RAxML 或 phyml)。我们仅使用最近邻交换(NNI)算法提出的重排结构,证明如果遇到多叉树,树搜索可能会过早终止。通过证明在实际数据中,树搜索过程中可能遇到的大多数可能的二分树实际上都是多叉树,这表明 NNI 的表现可能不佳,从而验证了这一结果的相关性。我们还表明,星形分解算法是另外两种流行的树搜索算法,即子树剪枝和重新连接(SPR)和树二分和重新连接(TBR)的特例,这意味着当它们遇到多叉树时,这两种算法可以有效地逃脱。我们警告不要使用 NNI 算法,并且对于大多数应用程序,我们建议使用更稳健的树搜索算法,例如 SPR 和 TBR。