PostProcessChain {Geneland}R Documentation

Computation for maps of posterior probability of population membership

Description

Computes posterior probabilities of population membership for each pixel of the spatial domain.

Usage

PostProcessChain(coordinates,genotypes,allele.numbers,
path.mcmc,nxdom, nydom,burnin)

Arguments

coordinates Spatial coordinates of individuals. A matrix with 2 columns and one line per individual.
genotypes Genotypes of individuals. A matrix with one line per individual and 2 columns per locus
allele.numbers A vector of integer containing the number of possible allele for each locus
path.mcmc Path to output files directory
nxdom Number of pixel for discretization of the spatial domain in the horizontal direction
nydom Number of pixel for discretization of the spatial domain in the vertical direction
burnin Number of iterations of the chain to throw away. WARNING : this argument should be given the number of stored iterations (and not the number of computed iterations which differ if burnin !=1). If you have nit=100000 and thinning=100, then only 1000 iterations are stored. Then burnin=10 will throw away 10 stored iterations, namely 1000*10 computed iterations.

Details

path.data’ directory should contain at least three files named exactly : ‘coordinates.txt’, ‘genotypes.txt’ and ‘allele.numbers.txt’ and containing respectively the spatial coordinates, the genotypes and the number of alleles per locus.

See format of files simulated by simFmodel for an example.

Value

Posterior probability of population membership for each pixel are written in an ascii file called ‘proba.pop.membership.txt’ (one column per population, npopmax values are computed for each pixel, pixels are stored row-wise starting from bottom left).
Another file called ‘proba.pop.membership.perm.txt’ tries to get rid of label switching issues by labelling the population according to a fixed constraint. (This has proved to be usefull with a small number of loci, (e.g. nloc=3), for well differentiated populations.)

Author(s)

Gilles Guillot

References

A spatial statistical model for landscape genetics, Guillot, Estoup, Mortier, Cosson, Genetics, 2005

Guillot, G., Geneland : A program for landscape genetics. Molecular Ecology Notes, submited.

See Also

PlotTessellation


[Package Geneland version 0.5 Index]