Alignment-free sequence comparison for virus genomes based on location correlation coefficient
[Display omitted] •A novel measure called L-step delay correlation coefficient is proposed to describe the correlation of nucleotide locations in viral genomes.•A 16×L-dimensional numerical vector consisting of L-step delay correlation coefficients is proposed to represent a virus genome efficiently...
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Veröffentlicht in: | Infection, genetics and evolution genetics and evolution, 2021-12, Vol.96, p.105106-105106, Article 105106 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | [Display omitted]
•A novel measure called L-step delay correlation coefficient is proposed to describe the correlation of nucleotide locations in viral genomes.•A 16×L-dimensional numerical vector consisting of L-step delay correlation coefficients is proposed to represent a virus genome efficiently.•Our results indicate that the new tool is fast in speed and accurate for inferring thephylogeny of organisms.
Coronaviruses (especially SARS-CoV-2) are characterized by rapid mutation and wide spread. As these characteristics easily lead to global pandemics, studying the evolutionary relationship between viruses is essential for clinical diagnosis. DNA sequencing has played an important role in evolutionary analysis. Recent alignment-free methods can overcome the problems of traditional alignment-based methods, which consume both time and space. This paper proposes a novel alignment-free method called the correlation coefficient feature vector (CCFV), which defines a correlation measure of the L-step delay of a nucleotide location from its location in the original DNA sequence. The numerical feature is a 16×L-dimensional numerical vector describing the distribution characteristics of the nucleotide positions in a DNA sequence. The proposed L-step delay correlation measure is interestingly related to some types of L+1 spaced mers. Unlike traditional gene comparison, our method avoids the computational complexity of multiple sequence alignment, and hence improves the speed of sequence comparison. Our method is applied to evolutionary analysis of the common human viruses including SARS-CoV-2, Dengue virus, Hepatitis B virus, and human rhinovirus and achieves the same or even better results than alignment-based methods. Especially for SARS-CoV-2, our method also confirms that bats are potential intermediate hosts of SARS-CoV-2. |
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ISSN: | 1567-1348 1567-7257 |
DOI: | 10.1016/j.meegid.2021.105106 |