A support vector machine based test for incongruence between sets of trees in tree space.
A support vector machine based test for incongruence between sets of trees in tree space.
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DOI：
10.1186/1471-2105-13-210
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发表时间：
2012-08-21
影响因子：
3
通讯作者：
Yoshida R
中科院分区：
文献类型：
--
作者：
Haws DC;Huggins P;O'Neill EM;Weisrock DW;Yoshida R
越来越多地使用多位点数据集进行系统发育重建，增加了确定一组基因树是否明显偏离其他基因的系统发育模式的需要。这种不寻常的基因树可能受到了其他进化过程的影响，如选择、基因复制或水平基因转移。受这个问题的启发，我们提出了两个基因树经验分布的非参数拟合度检验，并开发了软件GeneOut来估计检验的p值。我们的方法将树映射到多维向量空间，然后应用支持向量机(SVM)来度量两组预定义树之间的间隔。我们使用置换测试来评估支持向量机分离的重要性。为了演示GeneOut的性能，我们将其应用于不同物种树内的不同物种树深度的模拟基因树的比较。直接应用于大样本量的模拟基因树集合，GeneOut能够检测到在不同物种树下生成的两组基因树之间的非常微小的差异。我们的统计测试还可以通过各种系统发育最优化标准将树重建纳入其测试框架。当应用于来自不同基因树集合的模拟DNA序列数据时，以接收器操作特征(ROC)曲线的形式的结果表明，GeneOut在检测多维空间中不同分布的树集合之间的差异方面表现良好。此外，它还很好地控制了假阳性率和假阴性率，表明了很高的准确率。我们的统计检验的非参数性质提供了快速有效的分析，并使其适用于进化或其他因素可能导致树具有不同多维分布的任何情况。GeneOut软件是在GNU公共许可证下免费提供的。
The increased use of multi-locus data sets for phylogenetic reconstruction has increased the need to determine whether a set of gene trees significantly deviate from the phylogenetic patterns of other genes. Such unusual gene trees may have been influenced by other evolutionary processes such as selection, gene duplication, or horizontal gene transfer. Motivated by this problem we propose a nonparametric goodness-of-fit test for two empirical distributions of gene trees, and we developed the software GeneOut to estimate a p-value for the test. Our approach maps trees into a multi-dimensional vector space and then applies support vector machines (SVMs) to measure the separation between two sets of pre-defined trees. We use a permutation test to assess the significance of the SVM separation. To demonstrate the performance of GeneOut, we applied it to the comparison of gene trees simulated within different species trees across a range of species tree depths. Applied directly to sets of simulated gene trees with large sample sizes, GeneOut was able to detect very small differences between two set of gene trees generated under different species trees. Our statistical test can also include tree reconstruction into its test framework through a variety of phylogenetic optimality criteria. When applied to DNA sequence data simulated from different sets of gene trees, results in the form of receiver operating characteristic (ROC) curves indicated that GeneOut performed well in the detection of differences between sets of trees with different distributions in a multi-dimensional space. Furthermore, it controlled false positive and false negative rates very well, indicating a high degree of accuracy. The non-parametric nature of our statistical test provides fast and efficient analyses, and makes it an applicable test for any scenario where evolutionary or other factors can lead to trees with different multi-dimensional distributions. The software GeneOut is freely available under the GNU public license.
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影响因子：
6.5
作者：
Huelsenbeck, JP;Hillis, DM;Nielsen, R
通讯作者：
Nielsen, R
DOI：
10.2307/2413326
发表时间：
1985-01-01
期刊：
SYSTEMATIC ZOOLOGY
影响因子：
--
作者：
ESTABROOK, GF;MCMORRIS, FR;MEACHAM, CA
通讯作者：
MEACHAM, CA
影响因子：
3.3
作者：
FELSENSTEIN, J
通讯作者：
FELSENSTEIN, J
影响因子：
3.9
作者：
HASEGAWA, M;KISHINO, H;YANO, TA
通讯作者：
YANO, TA
影响因子：
6.5
作者：
Goldman, N;Anderson, JP;Rodrigo, AG
通讯作者：
Rodrigo, AG