Geneland {Geneland} | R Documentation |
The main function mcmcFmodel
takes geo-referenced individual multilocus genetic data and tries to detect
population structure, i.e sub-populations making use of both spatial and genetic information.
The overall population is viewed as a co-existence of sub-populations at Hardy-Weiberg equilibrium. The sub-populations are supposed to be spatially organised through the so-called colored Poisson-Voronoi tessellation. Allele frequencies are assumed to be drawn from the F-model as described in (Falush 2003) although the particular case of independent Dirichlet allele frequencies, as described by Pritchard (2000), is also handled. Individuals within populations are assumed to be randomly located and Hardy-Weinberg equilibrium and linkage equilibrium are assumed.
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 mcmcFmodel
.
Function PostProcessChain
read some output files of
mcmcFmodel
and computes some statistics suitable to print maps of inferred
populations.
See Storage format
section in mcmcFmodel help page.
The following functions are provided by the package:
simFmodel
: simulation from the prior of the spatial
F-model
mcmcFmodel
: 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 mcmcFmodel
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
Plotntile
: Graphical display of number of tiles along
MCMC run
PosteriorMode
: Computation and/or graphical display of
mode in the posterior distribution of class membership at each pixel
Fstat
: Computations of pairwise F statistics between
inferred subpopulations
FormatGenotypes
: Transform a file of genotypes into
a format suitable for function mcmcFmodel
setplot
: Internal function
rdiscr
: Internal function
Gilles Guillot
http://www.inapg.inra.fr/ens_rech/mathinfo/personnel/guillot/welcome.html
On the implementation of mixture models in population genetics:
- J.K. Pritchard, M. Stephens and P. Donnelly, Inference of population structure using multilocus genotype data, Genetics, pp 945-959 vol. 155, 2000
- Falush D., M. Stephens and J.K. Pritchard, Inference of population structure using multilocus genotype data: Linked loci and correlated allele frequencies, Genetics, pp 1567-1587, vol 164, 2003
On the implementation of variable dimension MCMC algorihtm in population genetics:
- Corander, J.C., Waldmann, P. and Sillanpaa, M.J., Bayesian analysis of genetic differentiation between populations, Genetics, 2003, 163, 367-374
- Corander, J.C., P. Waldmann, P. Martinen and M.J. Sillanpaa, , BAPS2: Enhanced possibilities for the analysis of genetic population structure, Bioinformatics, vol. 20,number 15, 2004
On the use of Voronoi tessellations in population genetics :
- Dupanloup, I., Schneider, S. and Excoffier, L., A simulated annealing approach to define genetic structure of populations, Molecular Ecology, 2002, 11, 2571-2581
On the model (and sub-models) implemented in Geneland
- Guillot G. A. Estoup, F. Mortier, J.F. Cosson, A spatial statistical model for landscape genetics, Genetics, 2005
- Guillot, G., Geneland : A program for landscape genetics. Molecular Ecology Notes, submited.