Abstract
The COVID-19 pandemic has underscored the need for fast and accurate epidemiology, particularly due to the high observed mutation frequency in SARS-CoV-2. This study aims to explore the evolution of SARS-CoV-2 through a global analysis. To facilitate a comparative analysis of temporal mutation data, we developed CovidTGI, a Shiny web application. CovidTGI provides insights into observed mutation frequencies and the temporal relationships among mutations across various clades in different geographical regions. Our tool relies on a database that includes 2 million samples obtained from the National Center for Biotechnology Information (NCBI), along with 500 in-house Sicilian samples collected between May 2021 and June 2022. From this smaller group of samples, we identified key variants that are prevalent within a specific clade. Our tool is designed to study the evolution of SARS-CoV-2, which clearly follows a complex trajectory. This complexity highlights the necessity for sophisticated tools like CovidTGI to understand and track the evolution of this virus.
Keywords:
Bioinformatics; Classification Description; Genetics.