LAMARC 2.0: maximum likelihood and Bayesian estimation of population parameters

TLDR

LAMARC 2.0 is a Markov chain Monte Carlo coalescent sampler that estimates population genetic parameters from genetic data. LAMARC 2.0 co‑estimates parameters such as Θ, migration, growth, and recombination using either maximum‑likelihood or Bayesian inference on nucleotide, SNP, microsatellite, or electrophoretic data, with or without resolved haplotypes. The software is distributed as portable source code and executables for Windows, macOS, and Linux. LAMARC 2.0 is freely available; contact [e-mail] for access.

Abstract

Abstract Summary: We present a Markov chain Monte Carlo coalescent genealogy sampler, LAMARC 2.0, which estimates population genetic parameters from genetic data. LAMARC can co-estimate subpopulation Θ = 4Neμ, immigration rates, subpopulation exponential growth rates and overall recombination rate, or a user-specified subset of these parameters. It can perform either maximum-likelihood or Bayesian analysis, and accomodates nucleotide sequence, SNP, microsatellite or elecrophoretic data, with resolved or unresolved haplotypes. It is available as portable source code and executables for all three major platforms. Availability: LAMARC 2.0 is freely available at Contact: [e-mail]