Rev Language Reference
dnMultiSpeciesCoalescent - Multispecies coalescent Distribution
Multispecies coalescent distribution describing how gene trees can be generated from within a species tree given a constant effective population size. Requires an ultrametric species tree, a single effective population size (a single real positive), and taxa with species and individual names.
Usage
Arguments
| speciesTree : | TimeTree (pass by const reference) |
| The species tree in which the gene trees evolve. | |
| Ne : | RealPos (pass by const reference) |
| The effective population size(s). | |
| taxa : | Taxon[] (pass by value) |
| The vector of taxa which have species and individual names. |
Domain Type
Details
The species tree must be ultrametric.
The effective population size is constant across the species tree.
Example
# We are going to save the trees we simulate in the folder simulatedTrees:
dataFolder = "simulatedTrees/"
# Let’s simulate a species tree with 10 taxa, 2 gene trees, 3 alleles per species:
n_species <- 10
n_genes <- 2
n_alleles <- 3
# we simulate an ultrametric species tree:
# Species names:
for (i in 1:n_species) {
species[i] <- taxon(taxonName="Species_"+i, speciesName="Species_"+i)
}
spTree ~ dnBirthDeath(lambda=0.3, mu=0.2, rootAge=10, rho=1, samplingStrategy="uniform", condition="nTaxa", taxa=species)
print(spTree)
# let's pick a constant effective population size of 50:
popSize <- 50
# let's simulate gene trees now:
# taxa names:
for (g in 1:n_genes) {
for (i in 1:n_species) {
for (j in 1:n_alleles) {
taxons[g][(i-1)*n_alleles+j] <- taxon(taxonName="Species_"+i+"_"+j, speciesName="Species_"+i)
}
}
geneTrees[g] ~ dnMultiSpeciesCoalescent(speciesTree=spTree, Ne=popSize, taxa=taxons[g])
print(geneTrees[g])
}
# We can save the species tree and the gene trees:
write(spTree, filename=dataFolder+"speciesTree")
# Saving the gene trees
for (i in 1:(n_genes)) {
write(geneTrees[i], filename=dataFolder+"geneTree_"+i+".tree")
}
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