RRphylo (version 3.0.0)

resampleTree: Altering phylogenetic trees

Description

The function alters the topology and randomly removes a user-specified proportion of species from a phylogenetic tree.

Usage

resampleTree(tree,s=0.25,sdata=NULL,nodes=NULL,categories=NULL,
             swap.si=0.1,swap.si2=0.1,swap.node=NULL,nsim=1)

Value

The function returns phylo or multiPhylo object. The output always has an attribute "Call" which returns an unevaluated call to the function.

Arguments

tree

a phylogenetic tree. The tree needs not to be ultrametric or fully dichotomous.

s

the percentage of tips to be cut off. It is set at 25% by default.

sdata

to be supplied to condition the species sampling. It can be either a named vector or a data.frame/matrix having the species names as first column. In case of stratified random sampling, sdata should contain the strata. Otherwise, the user can provide a sampling probability (meant as the probability to be removed from the tree) for each species.

nodes

the clades to be preserved. In this case the function maintains no less than 5 species at least in each of them.

categories

the categories to be preserved. In this case the function maintains no less than 5 species at least in each of them.

swap.si, swap.si2, swap.node

arguments si, si2, node as passed to swapONE. The default for both si and si2 is 0.1.

nsim

number of phylogenies to return. It is set at 1 by default.

Author

Silvia Castiglione, Giorgia Girardi

See Also

search.conv vignette; overfitRR vignette; Alternative-trees vignette

Examples

if (FALSE) {
DataCetaceans$treecet->treecet
plot(treecet,show.tip.label = FALSE,no.margin = TRUE)
nodelabels(frame="n",col="red")

# Select two clades for stratified random sampling
clanods=c("crown_Odo"=150,"crown_Mysti"=131)
sdata1<-do.call(rbind,lapply(1:length(clanods),function(w)
  data.frame(species=tips(treecet,clanods[w]),group=names(clanods)[w])))

# generate a vector of probabilities based on body mass
prdata<-max(DataCetaceans$masscet)-DataCetaceans$masscet

# select two nodes to be preserved
nn=c(180,159)

# generate two fictional categorical vectors to be preserved
cat1<-sample(rep(c("a","b","c"),each=39),Ntip(treecet))
names(cat1)<-treecet$tip.label
cat2<-rep(c("d","e"),each=100)
names(cat2)<-sample(treecet$tip.label,100)

# 1. Random sampling
resampleTree(treecet,s=0.25,swap.si=0.3)->treecet1

# 1.1 Random sampling preserving clades
resampleTree(treecet,s=0.25,nodes=nn)->treecet2

# 2. Stratified random sampling
resampleTree(treecet,sdata = sdata1,s=0.25)->treecet3

# 2.1 Stratified random sampling preserving clades and categories
resampleTree(treecet,sdata = sdata1,s=0.25,nodes=nn,categories = list(cat1,cat2))->treecet4

# 3. Sampling conditioned on probability
resampleTree(treecet,sdata = prdata,s=0.25,nsim=5)->treecet5
}