Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
BMC Bioinformatics. 2009 Dec 15;10:423. doi: 10.1186/1471-2105-10-423.
The understanding of evolutionary relationships is a fundamental aspect of modern biology, with the phylogenetic tree being a primary tool for describing these associations. However, comparison of trees for the purpose of assessing similarity and the quantification of various biological processes remains a significant challenge.
We describe a novel approach for the comparison of phylogenetic distance information based on the alignment of representative high-dimensional embeddings (xCEED: Comparison of Embedded Evolutionary Distances). The xCEED methodology, which utilizes multidimensional scaling and Procrustes-related superimposition approaches, provides the ability to measure the global similarity between trees as well as incongruities between them. We demonstrate the application of this approach to the prediction of coevolving protein interactions and demonstrate its improved performance over the mirrortree, tol-mirrortree, phylogenetic vector projection, and partial correlation approaches. Furthermore, we show its applicability to both the detection of horizontal gene transfer events as well as its potential use in the prediction of interaction specificity between a pair of multigene families.
These approaches provide additional tools for the study of phylogenetic trees and associated evolutionary processes. Source code is available at http://gomezlab.bme.unc.edu/tools.
进化关系的理解是现代生物学的一个基本方面，系统发育树是描述这些关系的主要工具。然而，为了评估相似性和量化各种生物学过程而比较树仍然是一个重大挑战。
我们描述了一种基于代表性高维嵌入排列的系统发育距离信息比较的新方法（xCEED：嵌入式进化距离比较）。xCEED 方法利用多维尺度和 Procrustes 相关叠加方法，能够测量树之间的全局相似性和它们之间的不协调性。我们展示了该方法在预测共进化蛋白质相互作用中的应用，并证明了它优于镜像树、tol-mirror 树、系统发育向量投影和偏相关方法的性能。此外，我们还展示了它在检测水平基因转移事件中的适用性，以及在预测一对多基因家族之间的相互作用特异性中的潜在用途。
这些方法为研究系统发育树和相关进化过程提供了额外的工具。源代码可在 http://gomezlab.bme.unc.edu/tools 获得。
