Author(s)

Dipendra C. Sengupta¹, Matthew D. Hill¹, Kevin R. Benton¹, Hirendra N. Banerjee²

¹Department of Mathematics, Computer Science & Engineering Technology, Elizabeth City State University, Elizabeth City, North Carolina, USA.
²Department Natural Sciences, Elizabeth City State University, Elizabeth City, North Carolina, USA.

The novel coronavirus (SARS-COV-2) is generally referred to as Covid-19 virus has spread to 213 countries with nearly 7 million confirmed cases and nearly 400,000 deaths. Such major outbreaks demand classification and origin of the virus genomic sequence, for planning, containment, and treatment. Motivated by the above need, we report two alignment-free methods combing with CGR to perform clustering analysis and create a phylogenetic tree based on it. To each DNA sequence we associate a matrix then define distance between two DNA sequences to be the distance between their associated matrix. These methods are being used for phylogenetic analysis of coronavirus sequences. Our approach provides a powerful tool for analyzing and annotating genomes and their phylogenetic relationships. We also compare our tool to ClustalX algorithm which is one of the most popular alignment methods. Our alignment-free methods are shown to be capable of finding closest genetic relatives of coronaviruses.

Covid-19, Chaos Game Representation, Deoxyribonucleic Acid, Phylogenetic Analysis, Shannon Entropy

Sengupta, D. , Hill, M. , Benton, K. and Banerjee, H. (2020) Similarity Studies of Corona Viruses through Chaos Game Representation. Computational Molecular Bioscience, 10, 61-72. doi: 10.4236/cmb.2020.103004.