rmetasim (version 3.1.14)

landscape.coalinput: Add loci and individuals based upon output from SimCoal 2.0

Description

Take rmetasim object and replaces the locus and individual data based on the results of a SimCoal run stored in Arlequin format files

Usage

## must be called AFTER integer, switch, and float params have been created
   landscape.coalinput(rland, npp=200, arlseq = NULL, arlms = NULL, seqsitemut=1e-7,
                               msmut = 5e-4, mut.rates = NULL)

Arguments

rland

partially created landscape object, required

npp

number per population. Scalar or vector of length equal to number of populations. If scalar, value replicated

arlseq

name of the Arlequin format file containing a single locus of haploid sequence data for any number of populations

arlms

name of the Arlequin format file containing a single locus of diploid microsatellite data for any number of populations

seqsitemut

mutation rate for sequence data

msmut

mutation rate for diploid genotypic data

mut.rates

alternative means to specify mutation rates. Legal values are either NULL or a vector of rates equal to the number of loci to simulate. If NULL, SSR loci are assigned msmut as a mutation rate and sequence-based loci, seqsitemut. If a vector, ovrrides msmut and seqsitemut

Value

an rmetasim object with new loci and individuals

Details

This function provides part of an interface between R and SimCoal, an environment for simulating sequences and microsatellite genotypes from coalescent trees. SimCoal can be used to simulate a standing crop of alleles and their relationships under a wide range of demographies. It returns haplotypes and genotypes of individuals in Arlequin format files.

If either 'arlseq' or 'arlms' are set to NULL, their corresponding data will not be included in the landscape (for example if arlseq=NULL, only diploid genotypes will be imported

The genotypes in the Arlequin files are used to create rland\$loci objects based upon their frequencies and states. These rland\$loci sub-objects are then used to populate the rland\$individuals sub-object.

The number of populations in the Arlequin files should be the same among genetic locus types (sequence versus microsatellite) and the rland\$intparam\$habitats parameter. The per-population frequency data will be used in creating individuals

Examples

# NOT RUN {
  exampleland <- landscape.new.empty()
  exampleland <- landscape.new.intparam(exampleland, s=2, h=2)
  exampleland <- landscape.new.floatparam(exampleland)
  exampleland <- landscape.new.switchparam(exampleland)

#  exampleland <- landscape.coalinput(exampleland)
#  exampleland$loci

# }