A simulation framework for modeling the within-patient evolutionary dynamics of SARS-CoV-2.

ABSTRACT: The global impact of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to considerable interest in detecting novel beneficial mutations and other genomic changes that may signal the development of variants of concern (VOCs). The ability to accurately detect these changes within individual patient samples is important in enabling early detection of VOCs. Such genomic scans for positive selection are best performed via comparison of empirical data to simulated data wherein evolutionary factors, including mutation and recombination rates, reproductive and infection dynamics, and purifying and background selection, can be carefully accounted for and parameterized. While there has been work to quantify these factors in SARS-CoV-2, they have yet to be integrated into a baselin

SUBMITTER: Terbot JW 

PROVIDER: S-EPMC10370031 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature