CodABC

CodABC estimates recombination, substitution (synonymous and nonsynonymous), and molecular adaptation rates in protein-coding sequences using approximate Bayesian computation.

Key Features:

• Joint Estimation: Integrates joint estimation of recombination, substitution (synonymous and nonsynonymous), and molecular adaptation rates from coding sequences.
• Approximate Bayesian Computation: Uses approximate Bayesian computation (ABC) to approximate posterior distributions without explicit likelihood calculations.
• Regression-Adjusted ABC: Implements regression-adjusted ABC to reduce bias and variance in parameter estimates.
• Model Flexibility: Supports a variety of codon models and accommodates intracodon recombination and longitudinal sampling.
• Nuisance Parameters: Incorporates nuisance parameters including codon frequencies, transition matrices, site heterogeneity, and invariable sites.
• Parallel Computing: Supports parallel execution on multicore machines for computationally intensive analyses.
• Comparative Performance: Often outperforms traditional maximum-likelihood methods that rely on more approximate models for recombining coding sequences.

Scientific Applications:

• Molecular Evolution: Estimates substitution and recombination rates to characterize evolutionary dynamics of protein-coding genes.
• Adaptive Evolution: Provides estimates of molecular adaptation rates to inform studies of adaptive evolution.
• Genetic Diversity: Facilitates inference of patterns of genetic diversity influenced by recombination and selection.
• Recombination Effects: Assesses the impact of recombination on gene function and fitness through joint parameter estimation.

Methodology:

Uses approximate Bayesian computation (standard ABC) to approximate posterior distributions, employs regression-adjusted ABC for improved parameter estimation, and utilizes parallel computing on multicore machines.