Similarity-weighted entropy for quantifying genetic diversity in viral quasispecies

A viral quasispecies is a genetically diverse population of closely related viral variants that exist in a state of dynamic equilibrium. This diversity, driven by mutations, recombination, and selective pressures, enables viruses to adapt rapidly, affecting pathogenicity and treatment resistance. Quantifying the genetic diversity within viral quasispecies is therefore crucial for understanding viral evolution and for designing effective therapeutic strategies. Entropy is a commonly used metric to measure genetic diversity within such populations; however, traditional entropy calculations often neglect genetic similarities between sequences, which can result in overestimating true diversity. In this study, I compare several widely used diversity indices for quantifying viral quasispecies diversity and introduce a novel similarity-weighted entropy metric that incorporates sequence similarity into entropy calculations. This approach enables a more comprehensive representation of diversity in genetically cohesive viral populations. By applying both conventional and similarity-weighted entropy calculations to hypothetical sequence populations and real viroid and virus quasispecies, I demonstrate that similarity-weighted entropy provides a more comprehensive measure of genetic diversity while maintaining the simplicity of conventional entropy. These findings highlight the value of similarity-weighted entropy in characterizing viral quasispecies and its potential to improve our understanding of viral adaptation and resistance mechanisms.