PostProcessMultChain {Geneland} | R Documentation |
Computes posterior probabilities of population membership for each pixel of the spatial domain.
PostProcessMultChain(coordinates,genotypes, path.all,nrun,nxdom, nydom,burnin)
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 |
path.all |
Path to output files directory |
nrun |
Number of runs |
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 100*10 computed iterations. |
Posterior probability of population membership for each pixel: |
They are
written in an ascii file called ‘proba.pop.membership.txt’
(one column per population,
npopmax values are computed for each pixel.
Images in each column of ‘proba.pop.membership.txt’ are stored
column-wise starting from the bottom left pixel.
First line of ‘proba.pop.membership.txt’ = bottom left pixel ,
second line of ‘proba.pop.membership.txt’ = upward neighboor of
the previous pixel, etc...)
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.) |
Posterior probability of population membership for each
individual: |
They are written in a file named ‘proba.pop.membership.indiv.txt’. |
Label of modal population for pixels and individuals: |
They are written in files named ‘modal.pop.txt’ and
‘modal.pop.indiv.txt’
respectively.
See the example section of function MCMC to see
how they can be added in a plot. |
Gilles Guillot
G. Guillot, Estoup, A., Mortier, F. Cosson, J.F. A spatial statistical model for landscape genetics. Genetics, 170, 1261-1280, 2005.
G. Guillot, Mortier, F., Estoup, A. Geneland : A program for landscape genetics. Molecular Ecology Notes, 5, 712-715, 2005.