Fractal correlations in the Covid-19 genome sequence via multivariate rescaled range analysis. (March 2023)

• Record Type: Journal Article
• Authors: Meraz, Monica; Carbó, Roxana; Rodriguez, Eduardo; Alvarez-Ramirez, Jose
• Is Part Of: Chaos, solitons and fractals. Volume 168(2023)
• Publication Date: 2023-03
• Subjects: Genome sequence -- Fractality -- Voss rule mapping -- Multivariate correlations, randomness; Chaotic behavior in systems -- Periodicals; Solitons -- Periodicals; Fractals -- Periodicals; Chaotic behavior in systems; Fractals; Solitons; Periodicals; 003.7
• DOI: 10.1016/j.chaos.2023.113132
• Languages: English
• ISSNs: 0960-0779

Abstract

Abstract: An approach based on fractal scaling analysis to characterize the organization of the Covid-19 genome sequences is presented in this work. The method is based on a multivariate version of the fractal rescaled range analysis implemented on a sliding window scheme to detect variations of long-range correlations over the genome sequence domains. As a preliminary step, the nucleotide sequence is mapped in a numerical sequence by following a Voss rule, resulting in a multichannel sequence represented as a binary matrix. Fractal correlations, quantified in terms of the Hurst exponent, depending on the region of the sequence, where the Covid-19 genome sequences are predominantly random, with some patches of weak long-range correlations. The analysis shows that the regions of randomness are more abundant in the Covid-19 sequences than in the primitive SARS sequence, which suggests that the Covid-19 virus possesses a more diverse genomic structure for replication and infection. The analysis constrained to the surface glycoprotein region shows that the Covid-19 sequence is less random as compared to the SARS sequence, which indicates that the Covid-19 virus can undergo more ordered replications of the spike protein. The Omicron variation exhibits an interesting pattern with some randomness similarities with the other SARS and the Covid-19 genome sequences. Overall, the results show that the multivariate rescaled range analysis provides a suitable framework to assess long-term correlations hidden in the internal organization of the Covid-19 genome sequence. Highlights: Genome sequences were mapped to a matrix of binary sequences. A multivariate version of the rescaled range analysis was used for analysis. Covid-19 genome sequences are mostly random, with isolated regions of correlations. Omicron variant exhibited the highest degree of multifractality.