4.7 Article

LAMARC 2.0: maximum likelihood and Bayesian estimation of population parameters

Journal

BIOINFORMATICS
Volume 22, Issue 6, Pages 768-770

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btk051

Keywords

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Funding

  1. NCI NIH HHS [5R01CM51929-11] Funding Source: Medline
  2. NIGMS NIH HHS [R01 GM051929, 5R01GM51929-11] Funding Source: Medline

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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.

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