markophylo

markophylo implements maximum-likelihood inference of discrete-character evolution on phylogenetic trees using continuous-time Markov chain models to estimate evolutionary rates and patterns from data such as restriction sites, gene family presence/absence, intron presence/absence, and gene family size.

Key Features:

• Continuous-time Markov chain models: Fits continuous-time Markov chain models with finite state spaces to discrete character data.
• Site rate variation: Supports site rate variation (rate heterogeneity) across characters.
• Site partitioning: Allows site partitioning to model different substitution processes across partitions.
• Branch-specific rates: Implements branch-specific rate models to capture heterogeneity across lineages.
• Non-stationary prior root probabilities: Incorporates non-stationary prior root probability modeling.
• Sampling-bias corrections: Provides corrections for sampling bias in discrete-character datasets.
• Efficient implementation: Core computational functions are implemented in C++ for performance.

Scientific Applications:

• Inference of evolutionary rates and patterns: Enables maximum-likelihood estimation of rates and patterns of discrete-character evolution on phylogenies.
• Analysis of discrete character types: Applicable to restriction sites, gene family presence/absence, intron presence/absence, and gene family size data.
• Modeling complex evolutionary scenarios: Supports analyses that require rate heterogeneity, partitioned sites, branch-specific evolution, and non-stationary root states.

Methodology:

Fits maximum-likelihood models using continuous-time Markov chains on phylogenetic trees within a probabilistic framework; core functions implemented in C++; supports finite state spaces, site rate variation, site partitioning, branch-specific rates, non-stationary prior root probabilities, and sampling-bias corrections.