An Information-Entropy Position-Weighted K-Mer Relative Measure for Whole Genome Phylogeny Reconstruction.

An Information-Entropy Position-Weighted K-Mer Relative Measure for Whole Genome Phylogeny Reconstruction.
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DOI:
10.3389/fgene.2021.766496
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发表时间:
2021
影响因子:
3.7
通讯作者:
Anh VV
Anh VV
中科院分区:
生物学3区
文献类型:
--
作者:
Wu YQ;Yu ZG;Tang RB;Han GS;Anh VV

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由于处理时间和空间复杂性的计算成本较高,比对方法在序列比对和系统发育重建方面面临着劣势。另一方面,无比对方法的计算成本很低,最近在生物信息学领域得到了普及。在这里,我们提出了一种新的基于全基因组序列的无比对进化树重建方法。其中一个关键部分是信息熵位置加权k-mer相对度量(IEPWRMkmer),它结合了本课题组提出的k-MERS的位置加权度量和k-MERS的频率信息熵。曼哈顿距离被用来计算物种之间的成对距离。最后,采用邻接法构建系统发育树。为了评估该方法的性能,我们对其他研究人员使用的两个数据集进行了系统发育分析。结果表明,IEPWRMkmer方法是有效和可靠的。我们的方法的源代码在https://github.com/wuyaoqun37/IEPWRMkmer上提供。
Alignment methods have faced disadvantages in sequence comparison and phylogeny reconstruction due to their high computational costs in handling time and space complexity. On the other hand, alignment-free methods incur low computational costs and have recently gained popularity in the field of bioinformatics. Here we propose a new alignment-free method for phylogenetic tree reconstruction based on whole genome sequences. A key component is a measure called information-entropy position-weighted k-mer relative measure (IEPWRMkmer), which combines the position-weighted measure of k-mers proposed by our group and the information entropy of frequency of k-mers. The Manhattan distance is used to calculate the pairwise distance between species. Finally, we use the Neighbor-Joining method to construct the phylogenetic tree. To evaluate the performance of this method, we perform phylogenetic analysis on two datasets used by other researchers. The results demonstrate that the IEPWRMkmer method is efficient and reliable. The source codes of our method are provided at https://github.com/ wuyaoqun37/IEPWRMkmer.
DOI: 10.1073/pnas.83.14.5155
发表时间: 1986-07-01
影响因子: 11.1
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