Time Series Analysis of SARS-CoV-2 Genomes and Correlations among Highly Prevalent Mutations.

ABSTRACT: The efforts of the scientific community to tame the recent pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seem to have been diluted by the emergence of new viral strains. Therefore, it is imperative to understand the effect of mutations on viral evolution. We performed a time series analysis on 59,541 SARS-CoV-2 genomic sequences from around the world to gain insights into the kinetics of the mutations arising in the viral genomes. These 59,541 genomes were grouped according to month (January 2020 to March 2021) based on the collection date. Meta-analysis of these data led us to identify significant mutations in viral genomes. Pearson correlation of these mutations led us to the identification of 16 comutations. Among these comutations, some of the individu

SUBMITTER: Periwal N 

PROVIDER: S-EPMC9603882 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature