SMS

SMS selects the best substitution matrix and among-site rate model for phylogenetic analysis using likelihood-based criteria such as the Akaike Information Criterion (AIC).

Key Features:

• Model selection scope: Evaluates substitution matrices and rate variation models across sites for phylogenetic analyses.
• Likelihood-based criteria: Uses likelihood-based model selection metrics, explicitly including the Akaike Information Criterion (AIC).
• Efficient heuristics: Implements heuristics to reduce the need for exhaustive testing of all model combinations, achieving approximately a 50% reduction in runtime.
• PhyML integration: Operates within the PhyML environment to integrate model selection with PhyML-based phylogenetic workflows.
• Benchmarking: Has been evaluated against ProtTest and jModelTest2, producing results comparable to those tools.

Scientific Applications:

• Phylogenetic model selection: Determines substitution and among-site rate models for downstream phylogenetic tree inference and likelihood-based analyses.
• Large-scale phylogenetics: Enables model selection for large datasets where computational resources and runtime are limiting factors.
• Method comparison and benchmarking: Serves as an alternative for comparative evaluation against established tools such as ProtTest and jModelTest2.

Methodology:

Evaluates combinations of substitution matrices and among-site rate models using likelihood-based criteria (AIC) and applies heuristics to avoid exhaustive model testing, implemented within PhyML.