Visual and Quantitative Analyses of Virus Genomic Sequences using a Metric-based Algorithm

Abstract

This work aims to study the virus RNAs using a novel algorithm for accelerated exploring any-length genomic fragments in sequences using Hamming distance between the binary-expressed characters of an RNA and query patterns. The found repetitive genomic sub-sequences of different lengths were placed on one plot as genomic trajectories (walks) to increase the effectiveness of geometrical multi-scale genomic studies. Primary attention was paid to the building and analysis of the atg-triplet walks composing the schemes or skeletons of the viral RNAs. The 1-D distributions of these codon-starting atg-triplets were built with the single-symbol walks for full-scale analyses. The visual examination was followed by calculating statistical parameters of genomic sequences, including the estimation of geometry deviation and fractal properties of inter-atg distances. This approach was applied to the SARS CoV-2, MERS CoV, Dengue and Ebola viruses, whose complete genomic sequences are taken from GenBank and GISAID databases. The relative stability of these distributions for SARS CoV-2 and MERS CoV viruses was found, unlike the Dengue and Ebola distributions that showed an increased deviation of their geometrical and fractal characteristics of atg-distributions. The results of this work can found in classification of the virus families and in the study of their mutation.