LAMARC 2.0: maximum likelihood and Bayesian estimation of population parameters
Human Genome Sciences (United States) · University of Washington
Abstract
UNLABELLED: 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. AVAILABILITY: LAMARC 2.0 is freely available at http://evolution.gs.washington.edu/lamarc
Citation impact
- FWCI
- 22.02
- Percentile
- 100%
- References
- 11
Authors
1Topics & keywords
- Coalescent theory
- Markov chain Monte Carlo
- Bayesian probability
- Executable
- Population
- Markov chain
- Maximum likelihood
- Haplotype
- Reduced inequalities