Evaluation of Different Molecular Clock Models in a Mycobacterium Tuberculosis dataset

Abstract

Mycobacterium tuberculosis (MTB), as the causative agent of tuberculosis, continues to pose a significant global health threat. The rate of evolution within MTB remains a contentious issue, marked by divergent estimates from studies utilizing different calibration methods. Molecular clock models are statistical models used to estimate evolutionary rates and divergence times in various genome sequence data. These methods have been applied to various genomic data sets, including those from pathogens like MTB, viruses, and other organisms. However, there is a lack of consensus on the rate of evolution of MTB among different studies. These discrepancies in these estimates arise when different metrics are employed, indicating potential variation in the evolutionary tree’s evolution rates.