title: LAMARC 2.0: maximum likelihood and Bayesian estimation of population parameters.
abstract: 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 Theta = 4N(e)mu, 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.
  
  
  BACKGROUND
  LAMARC 2.0 is freely available at http://evolution.gs.washington.edu/lamarc
authors.affiliation: Department of Genome Sciences Box 357730 University of Washington Seattle, 98195-7730, USA. lamarc@gs.washington.edu
authors.forename: Mary K
authors.initials: MK
authors.lastname: Kuhner
mesh_terms: D001499:Bayes Theorem; D005075:Biological Evolution; D002874:Chromosome Mapping / Q000379:methods*; D003198:Computer Simulation; D004252:DNA Mutational Analysis / Q000379:methods*; D014644:Genetic Variation / Q000235:genetics; D005828:Genetics, Population / Q000379:methods*; D016013:Likelihood Functions; D008957:Models, Genetic; D015233:Models, Statistical; D012984:Software