Geneland-package: Simulation and inference for subdivided populations

Description Details Author(s) References


Detect population structure (i.e sub-populations), making use of genetic (and optionally geographic) information.


The main purpose of the program is to perform Bayesian inference of all the parameters involved through Markov Chain Monte-Carlo simulation. This is achievied by the function MCMC. Function PostProcessChain read some output files of MCMC and computes some statistics suitable to print maps of inferred populations.

See Storage format section in MCMC help page.

The following functions are provided by the package:

simFmodel: simulation from the prior of the spatial F-model

simdata: Simulation of georeferenced genotypes under an IBD + barrier model

show.simdata: Graphical display of data simulated by simdata

MCMC: Full Bayesian Markov Chain Monte Carlo inference of parameters in the spatial F-model

PostProcessChain: Post-procesing of MCMC output for maps of posterior probability of populations subdomains

PlotTessellation: Graphical display of inferred sub-domains

The following functions are very basic and are only intended to be an aid for those not familiar with R. Most probably you may want to use directly the output files of MCMC and PostProcessChain to print your own figures.

PlotDrift: Graphical display of drift factors along MCMC run

PlotFreqA: Graphical display of allele frequencies in the ancestral population along MCMC run

PlotFreq: Graphical display of allele frequencies in the present time population along MCMC run

Plotnpop: Graphical display of number of populations along MCMC run

Package: Geneland
Type: Package
License: GPL


Arnaud Estoup, Gilles Guillot, Filipe Santos

See also


Geneland documentation built on April 14, 2017, 2:31 p.m.