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滑动贝叶斯法:基于贝叶斯系统发育推断,采用滑动窗口方法探索重组现象。

SlidingBayes: exploring recombination using a sliding window approach based on Bayesian phylogenetic inference.

作者信息

Paraskevis D, Deforche K, Lemey P, Magiorkinis G, Hatzakis A, Vandamme A-M

机构信息

Laboratory for Clinical and Epidemiological Virology, Rega Institute for Medical Research, Katholieke Universiteit Leuven, Minderbroedersstraat 10, B-3000 Leuven, Belgium.

出版信息

Bioinformatics. 2005 Apr 1;21(7):1274-5. doi: 10.1093/bioinformatics/bti139. Epub 2004 Nov 16.

Abstract

We developed a software tool (SlidingBayes) for recombination analysis based on Bayesian phylogenetic inference. Sliding-Bayes provides a powerful approach for detecting potential recombination, especially between highly divergent sequences and complex HIV-1 recombinants for which simpler methods like neighbor joining (NJ) may be less powerful. SlidingBayes guides Markov Chain Monte Carlo (MCMC) sampling performed by MrBayes in a sliding window across the alignment (Bayesian scanning). The tool can be used for nucleotide and amino acid sequences and combines all the modeling possibilities of MrBayes with the ability to plot the posterior probability support for clustering of various combinations of taxa.

摘要

我们开发了一种基于贝叶斯系统发育推断的用于重组分析的软件工具(滑动贝叶斯)。滑动贝叶斯为检测潜在重组提供了一种强大的方法,特别是对于高度分化的序列之间以及复杂的HIV-1重组体,对于这些情况,像邻接法(NJ)这样的简单方法可能效力较弱。滑动贝叶斯指导MrBayes在比对上以滑动窗口进行马尔可夫链蒙特卡罗(MCMC)采样(贝叶斯扫描)。该工具可用于核苷酸和氨基酸序列,并将MrBayes的所有建模可能性与绘制不同分类群组合聚类的后验概率支持的能力相结合。

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