phylodyn

phylodyn estimates effective population size trajectories from gene genealogies using Bayesian nonparametric methods.

Key Features:

• Bayesian Nonparametric Estimation: Implements Bayesian nonparametric estimation of effective population size fluctuations over time.
• Markov Chain Monte Carlo (MCMC) Methods: Provides MCMC algorithms for sampling from complex posterior distributions.
• Integrated Nested Laplace Approximation (INLA): Incorporates INLA-based approaches to approximate posterior distributions as an efficient alternative to MCMC.
• Genealogical Data Handling: Processes timed genealogical data describing ancestral relationships and supports isochronous and heterochronous sampling.
• Preferential Sampling Models: Models sampling intensity as dependent on the effective population size trajectory.
• Generative Models: Assumes coalescent and sequentially Markov coalescent processes as generative models for genealogies.
• Simulation Functions: Includes coalescent simulation functions for conducting simulation studies with genealogies.

Scientific Applications:

• Evolutionary Biology: Infers temporal changes in population size for evolutionary analyses.
• Population Genetics: Reconstructs demographic history and population-size dynamics in population genetics studies.
• Pathogen Evolution: Studies pathogen evolutionary dynamics by inferring epidemic population-size changes from genealogies.
• Conservation Genetics: Informs conservation assessments via historical population-size inference.
• Historical Demography: Reconstructs species' historical demography from genealogical data.

Methodology:

Applies Bayesian nonparametric estimation to genealogical data using MCMC and INLA, with coalescent and sequentially Markov coalescent generative models, preferential sampling models, and coalescent simulation functions.