R: Disentangling the contributions of geographic and ecological...
BEDASSLE-package
R Documentation
Disentangling the contributions of geographic and ecological isolation to genetic
differentiation
Description
This method models the covariance in allele frequencies between populations on a
landscape as a decreasing function of their pairwise geographic and ecological distance.
Allele frequencies are modeled as a spatial Gaussian process with a parametric covariance
function. The parameters of this covariance function, as well as the spatially smoothed
allele frequencies, are estimated in a custom Markov chain Monte Carlo.
Details
Package:
BEDASSLE
Type:
Package
Version:
1.5
Date:
2013-09-12
License:
GPL (>=2)
The two inference functions are MCMC and MCMC_BB, which call the
Markov chain Monte Carlo algorithms on the standard and overdispersion (Beta-Binomial)
models, respectively. To evaluate MCMC performance, there are a number of MCMC diagnosis
and visualization functions, which variously show the trace, plots, marginal and joint
marginal densities, and parameter acceptance rates. To evaluate model adequacy, there is
a posterior predictive sample function (posterior.predictive.sample), and an
accompanying function to plot its output and visually assess the model's ability to
describe the user's data.
Bradburd, G.S., Ralph, P.L., and Coop, G.M. Disentangling the effects of geographic and
ecological isolation on genetic differentiation. Evolution 2013.