ProteinEvolverABC

ProteinEvolverABC is a comprehensive computational framework designed to fill a significant gap in evolutionary biology: the estimation of recombination and substitution rates in protein sequences. This area, critical for understanding molecular diversity and the forces shaping it, has seen limited exploration, particularly in comparison to nucleotide sequence analysis. The framework leverages the power of approximate Bayesian computation (ABC), with options for regression adjustments, to derive these estimations from protein sequence alignments. It supports various protein evolution substitution models, demographic settings, and sampling strategies, accommodating the complexity and variability inherent in evolutionary studies.

Key features of ProteinEvolverABC include its ability to handle heterogeneous amino acid frequencies, varying rates of change among sites, and the proportion of invariable sites, enhancing the accuracy of its analyses. The framework has been tested across various evolutionary scenarios, demonstrating its capacity for accurate co-estimation of recombination and substitution rates. Its utility is exemplified through applications to several viral protein families, including coronaviruses, where it revealed diverse substitution and recombination rates.