ProteinEvolverABC

ProteinEvolverABC estimates recombination and substitution rates from alignments of protein sequences to coestimate evolutionary parameters using Approximate Bayesian Computation.

Key Features:

• Approximate Bayesian Computation: Implements Approximate Bayesian Computation for statistical inference, including standard ABC and regression-adjusted ABC, to estimate recombination and substitution rates.
• Substitution Models: Incorporates a variety of protein substitution models and accommodates diverse demographic scenarios and longitudinal sampling.
• Nuisance Parameters: Accounts for heterogeneous amino acid frequencies, variable rates among sites, and the proportion of invariant sites as nuisance parameters.
• Parallel Processing: Executes simulations in parallel on multicore machines to accelerate computation for large datasets.

Scientific Applications:

• Viral protein analysis: Applied to viral protein families, including coronaviruses, to assess heterogeneous substitution and recombination rates.
• Evolutionary parameter inference: Enables coestimation of evolutionary parameters to support inference of molecular diversity and underlying evolutionary processes in proteins.

Methodology:

Uses Approximate Bayesian Computation (standard and regression-adjusted) with protein substitution models, accounts for nuisance parameters (heterogeneous amino acid frequencies, among-site rate variation, invariant sites), and runs simulations in parallel on multicore machines.