Non-linear regression models for Approximate Bayesian Computation
Statistics and Computing
| Hi-index | 3.84 |
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 http://evolution.gs.washington.edu/lamarc Contact: lamarc@gs.washington.edu