Kosakovsky Pond Sergei L, Posada David, Gravenor Michael B, Woelk Christopher H, Frost Simon D W
Department of Pathology, University of California San Diego, La Jolla, CA 92093, USA.
Bioinformatics. 2006 Dec 15;22(24):3096-8. doi: 10.1093/bioinformatics/btl474. Epub 2006 Nov 16.
Phylogenetic and evolutionary inference can be severely misled if recombination is not accounted for, hence screening for it should be an essential component of nearly every comparative study. The evolution of recombinant sequences can not be properly explained by a single phylogenetic tree, but several phylogenies may be used to correctly model the evolution of non-recombinant fragments.
We developed a likelihood-based model selection procedure that uses a genetic algorithm to search multiple sequence alignments for evidence of recombination breakpoints and identify putative recombinant sequences. GARD is an extensible and intuitive method that can be run efficiently in parallel. Extensive simulation studies show that the method nearly always outperforms other available tools, both in terms of power and accuracy and that the use of GARD to screen sequences for recombination ensures good statistical properties for methods aimed at detecting positive selection.
Freely available http://www.datamonkey.org/GARD/
如果不考虑重组情况，系统发育和进化推断可能会被严重误导，因此，几乎在每一项比较研究中，对重组进行筛查都应是必不可少的一部分。重组序列的进化不能通过单一的系统发育树来恰当解释，但可以使用多个系统发育树来正确模拟非重组片段的进化。
我们开发了一种基于似然的模型选择程序，该程序使用遗传算法在多序列比对中搜索重组断点的证据并识别推定的重组序列。GARD是一种可扩展且直观的方法，能够高效并行运行。大量模拟研究表明，该方法在功效和准确性方面几乎总是优于其他现有工具，并且使用GARD对序列进行重组筛查可为旨在检测正选择的方法确保良好的统计特性。
