Buendia Patricia, Narasimhan Giri
Bioinformatics Research Group (BioRG), School of Computer Science, Florida International University, Miami, 33199, USA.
Proc IEEE Comput Syst Bioinform Conf. 2004:110-9.
A new computational method to study within-host viral evolution is explored to better understand the evolution and pathogenesis of viruses. Traditional phylogenetic tree methods are better suited to study relationships between contemporaneous species, which appear as leaves of a phylogenetic tree. However, viral sequences are often sampled serially from a single host. Consequently, data may be available at the leaves as well as the internal nodes of a phylogenetic tree. Recombination may further complicate the analysis. Such relationships are not easily expressed by traditional phylogenetic methods. We propose a new algorithm, called MinPD, based on minimum pairwise distances. Our algorithm uses multiple distance matrices and correlation rules to output a MinPD tree or network. We test our algorithm using extensive simmulations and apply it to a set of HIV sequence data isolated from one patient over a period of ten years. The proposed visualization of the phylogenetic tree\network further enhances the benefits of our methods.
探索了一种研究宿主体内病毒进化的新计算方法,以更好地理解病毒的进化和发病机制。传统的系统发育树方法更适合研究同时期物种之间的关系,这些物种表现为系统发育树的叶子。然而,病毒序列通常是从单个宿主中连续采样的。因此,数据可能在系统发育树的叶子以及内部节点处可用。重组可能会使分析进一步复杂化。这种关系不容易用传统的系统发育方法来表达。我们提出了一种基于最小成对距离的新算法,称为MinPD。我们的算法使用多个距离矩阵和相关规则来输出一个MinPD树或网络。我们通过广泛的模拟测试我们的算法,并将其应用于一组在十年期间从一名患者分离出的HIV序列数据。所提出的系统发育树/网络可视化进一步增强了我们方法的优势。