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Bioinformatics Advance Access originally published online on January 12, 2006
Bioinformatics 2006 22(6):768-770; doi:10.1093/bioinformatics/btk051
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LAMARC 2.0: maximum likelihood and Bayesian estimation of population parameters

Mary K. Kuhner 1

1Department of Genome Sciences Box 357730 University of Washington Seattle, WA 98195-7730, USA

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 {Theta} = 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 http://evolution.gs.washington.edu/lamarc

Contact: lamarc{at}gs.washington.edu

Received on November 15, 2005; revised on January 9, 2006; accepted on January 9, 2006

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