Running Coalescent Analyses With coalescentMCMC

Coalescent analyses have emerged in the recent years as a powerful approach to investigate the demography of populations using genetic data. The coalescent is a random process describing the coalescent times of a genealogy with respect to population size and mutation rate. In the majority of cases, the genealogy of individuals within a population is unknown. So a coalescent analysis typically integrates over the “likely ” genealogies to make inference on the dynamics of the population. This uses computer-intensive methods such as Monte Carlo simulations of Markov chains. Besides, if priors are defined on the distributions of the parameters, Bayesian inference can be done. Several methods have been proposed for such integrations, although currently there is no consensus on which method is the best, or which ones are the most appropriate in some circumstances [1]. coalescentMCMC aims to provide a general framework to run coalescent anal-yses. In its current version, the package provides a simple MCMC algorithm based on Hastings’s ratio