ModelTest

ModelTest selects the best-fitting model of nucleotide substitution for phylogenetic data to enable accurate modeling of DNA evolution and reliable phylogenetic inference.

Key Features:

• Log Likelihood Scores: Evaluates model fit using log-likelihood scores to quantitatively compare candidate nucleotide substitution models.
• Hierarchical Testing Framework: Performs hierarchical likelihood ratio tests to compare nested models and assess whether additional parameters significantly improve fit.
• Information Criteria: Computes Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to balance model fit and complexity.
• Model Selection Uncertainty Assessment: Produces statistical outputs that quantify uncertainty in model choice and supports model averaging across competing models.

Scientific Applications:

• Phylogenetic model selection: Identifies the most appropriate nucleotide substitution model for downstream phylogenetic analyses.
• Phylogenetic inference and tree estimation: Improves accuracy of phylogenetic trees and evolutionary hypotheses derived from molecular sequence data by using appropriate substitution models.
• Comparative and complex-evolution studies: Applied in analyses involving diverse taxa or complex evolutionary scenarios where model misspecification can bias conclusions.

Methodology:

Uses log-likelihood scoring, hierarchical likelihood ratio tests, AIC and BIC calculations, and statistical outputs for uncertainty assessment including metrics for model averaging.