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Whole genome single-nucleotide variation profile-based phylogenetic tree building methods for analysis of viral, bacterial and human genomes

机译:基于全基因组单核苷酸变异谱的系统发育树构建方法,用于分析病毒,细菌和人类基因组

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摘要

Next-generation sequencing data can be mapped to a reference genome to identify single-nucleotide polymorphisms/variations (SNPs/SNVs; called SNPs hereafter). In theory, SNPs can be compared across several samples and the differences can be used to create phylogenetic trees depicting relatedness among the samples. However, in practice this is difficult because currently there is no stand-alone tool that takes SNP data directly as input and produces phylogenetic trees. In response to this need, PhyloSNP application was created with two analysis methods 1) a quantitative method that creates the presence/absence matrix which can be directly used to generate phylogenetic trees or creates a tree from a shrunk genome alignment (includes additional bases surrounding the SNP position) and 2) a qualitative method that clusters samples based on the frequency of different bases found at a particular position. The algorithms were used to generate trees from Poliovirus, Burkholderia and human cancer genomics NGS datasets.Availability: PhyloSNP is freely available for download at http://hive.biochemistry.gwu.edu/dna.cgi?cmd=phylosnp.
机译:可以将下一代测序数据映射到参考基因组,以鉴定单核苷酸多态性/变异(SNP / SNV;此后称为SNP)。从理论上讲,可以在多个样本之间比较SNP,并且可以使用差异来创建描述样本之间相关性的系统树。但是,在实践中这很困难,因为当前没有独立的工具可以直接将SNP数据作为输入并生成系统树。为响应此需求,PhyloSNP应用程序通过两种分析方法创建:1)一种定量方法,该方法创建存在/不存在矩阵,该矩阵可直接用于生成系统发育树或从收缩的基因组比对中创建树(包括周围的其他碱基) SNP位置)和2)一种定性方法,该方法基于在特定位置发现的不同碱基的频率对样本进行聚类。该算法用于从脊髓灰质炎病毒,伯克霍尔德氏菌和人类癌症基因组学NGS数据集生成树木。

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