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The aim of the study is to analyze viruses using parameters obtained fromdistributions of nucleotide sequences in the viral RNA. Seeking for the inputdata homogeneity, we analyze single-stranded RNA viruses only. Two approachesare used to obtain the nucleotide sequences; In the first one, chunks of equallength (four nucleotides) are considered. In the second approach, the whole RNAgenome is divided into parts by adenine or the most frequent nucleotide as a"space". Rank--frequency distributions are studied in both cases. Within thefirst approach, the P\'olya and the negative hypergeometric distribution yieldthe best fit. For the distributions obtained within the second approach, wehave calculated a set of parameters, including entropy, mean sequence length,and its dispersion. The calculated parameters became the basis for theclassification of viruses. We observed that proximity of viruses on planesspanned on various pairs of parameters corresponds to related species. Incertain cases, such a proximity is observed for unrelated species as wellcalling thus for the expansion of the set of parameters used in theclassification. We also observed that the fourth most frequent nucleotidesequences obtained within the second approach are of different nature in caseof human coronaviruses (different nucleotides for MERS, SARS-CoV, andSARS-CoV-2 versus identical nucleotides for four other coronaviruses). Weexpect that our findings will be useful as a supplementary tool in theclassification of diseases caused by RNA viruses with respect to severity andcontagiousness.

On the verge of life: Distribution of nucleotide sequences in viral RNAs