simdata: Simulation of georeferenced genotypes under an IBD + barrier...
In Geneland: Detection of Structure from Multilocus Genetic Data

Description Usage Arguments Value Author(s) References See Also Examples

Simulates coordinates and genotypes for a npop populations. Each population is supposed to be under an Isolation by Distance model and different populations are supposed to be separated by impermeable barriers. The barriers are given by a Poisson-Voronoi tessellation.

            simdata(nindiv,
                    coord.indiv,
                    coord.lim=c(0,1,0,1),
                    npop,
                    rate,                        
                    number.nuclei,
                    coord.nuclei,
                    color.nuclei,
                    allele.numbers,
                    sim.gen=FALSE,
                    IBD=TRUE,
                    model="stable",
                    alpha=1,
                    beta=1,
                    gamma=1.8,
                    sim.quanti=FALSE,
                    nquanti.var,
                    mean.quanti,
                    sd.quanti,
                    seed.coord,
                    seed.tess,
                    seed.freq,
                    give.tess.grid=FALSE,
                    give.freq.grid=FALSE,
                    npix,
                    comp.Fst=FALSE,
                    comp.Dsigma2=FALSE,
                    comp.diff=FALSE,
                    width,
                    plot.pairs.borders=FALSE)

`nindiv`	Number of indivuals
`coord.indiv`	Coordinates of the individuals
`coord.lim`	Limits of the geographical domain. The domain is supposed to be rectangular and the limits are given as (abs min, abs max, ord min, ord max)
`npop`	Number of Populations
`rate`	Rate of the Poisson process governing the hidden tessellation
`number.nuclei`	Number of nuclei in the tessellation (if given, then `rate` is ignored)
`coord.nuclei`	Coordinates of the nuclei (the number of coordinates of the nuclei given here as a matrix has to comply with `number.nuclei` )
`color.nuclei`	Population membeship of the nuclei: a vector of integer of length `number of nuclei` whose values are between 1 and `npop`
`sim.gen`	Logical to say whether genetic data should be simulated
`allele.numbers`	A vector giving the number of alleles observed at each locus
`IBD`	Logical. If TRUE, then the allele frequencies are simulated according to an IBD model. If FALSE, panmixia is assumed.
`model`	Model of spatial covariance function used for the underlying Gaussian fields (see documentation of package `RandomFields` for details)
`alpha`	Parameter of the spatial Dirichlet vector field of frequencies (a positive real)
`beta`	Scale parameter of the spatial covariance function used for the underlying Gaussian fields. A positive real number (see documentation of package `RandomFields` for details)
`gamma`	Smoothing parameter of spatial covariance function used for the underlying Gaussian fields. (see documentation of package `RandomFields` for details)
`sim.quanti`	Logical to say whether quantitative data should be simulated
`nquanti.var`	Number of quantitative variables to be simulated
`mean.quanti`	Mean of the quantitative variables in the various groups. A matrix with `npop` lines and `nvar.quant` columns
`sd.quanti`	Standard deviation of the quantitative variables in the various groups. A matrix with `npop` lines and `nvar.quant` columns
`seed.coord`	Random seed to initialise the simulation of the coordinates (mostly for debugging)
`seed.tess`	Random seed to initialise the simulation of the tessellation (mostly for debugging)
`seed.freq`	Random seed to initialise the simulation of the frequencies (mostly for debugging)
`give.freq.grid`	Logical to tell whether frequencies on a grid are also returned
`give.tess.grid`	Logical to tell whether population memberships of pixels on a grid are also returned
`npix`	A vector of two integers telling how many horizontal and vertical pixel should contain the grid for the graphical representations
`comp.Fst`	Logical to tell whether Fst, Fis and Fit should be computed
`comp.Dsigma2`	Logical to tell whether IBD index Dsgma2 should be computed
`comp.diff`	Logical to tell whether the local differentiation across the barriers should be computed
`width`	Real number specifying the width around the barrier in the computation of its local differentiation
`plot.pairs.borders`	Logical to tell whether the pairs of individuals coming into the computation of the differentiation of the barriers should be plotted

A list whose components can be seen using summary

Arnaud Estoup, Gilles Guillot, Filipe Santos

G. Guillot, F. Santos, A. Estoup. Inference in population genetics with Geneland: a sensitivity analysis to spatial sampling scheme, null alleles and isolation by distance. Submitted.

Function show.simdata to make graphical display of simulated data.

## Not run: 
dataset <- simdata(nindiv=100,
             sim.gen=TRUE,
             number.nuclei=10,
             allele.numbers=rep(5,3),
             model="stable",
             IBD=TRUE,
             alpha=1,
             beta=1,
             gamma=1,
             npop=3,
             sim.gen=TRUE,
             give.tess.grid=TRUE,
             give.freq.grid=TRUE,
             npix=c(10,10),
             comp.Fst=TRUE,
             comp.Dsigma2=TRUE,
             comp.diff=TRUE,
             width=0.1,
             plot.pairs.borders=TRUE)

## End(Not run)