recluster.multi {recluster}

Multiscale bootstrap based on a consensus tree

Description

Given an initial tree and a data matrix, this function computes bootstrap for nodes as done by recluster.boot. Different levels of bootstrap can be computed by varying the proportions of species sampled from the original matrix.

Usage

recluster.multi(tree, mat, phylo = NULL, tr = 100, p = 0.5, 
dist = "simpson", method = "average", boot = 1000, levels = 2, step = 1)

Arguments

tree

A reference phylo tree for sites presumably constructed with recluster.cons function.

mat

The matrix used to construct the tree.

phylo

An ultrametric and rooted phylo tree for species having the same labels as in mat columns. Only required for phylogenetic beta-diversity indexes.

tr

The number of trees to be included in the consensus.

p

A numeric value between 0.5 and 1 giving the proportion for a clade to be represented in the consensus tree.

dist

One among the twelve beta-diversity indexes "simpson" "sorensen" "nestedness" "beta3" "richness" "jaccard" "phylosor" "phylosort" "phylosorpd" "unifrac" "unifract" "unifractpd". Any custom binary dissimilarity can also be specified according to the syntax of designdist function of the vegan package.

method

Any clustering method allowed by hclust.

boot

The number of trees used for bootstrap computation.

levels

The number of levels to be used in multiscale bootstrap.

step

The increase in ratio between the first level (x1) and the next ones.

Details

Computation can be time consuming. It is suggested to assess the degree of row bias by recluster.hist and recluster.node.strength to optimize the number of consensus trees before starting the analysis.

Value

A matrix indicating the percentage of bootstrap trees replicating each node for each level.

Author(s)

Leonardo Dapporto and Matteo Ramazzotti

References

Dapporto L., Ramazzotti M., Fattorini S., Talavera G., Vila R., Dennis R. "recluster: an unbiased clustering procedure for beta-diversity turnover" Ecography (2013), 36:1070-1075.

Examples

data(datamod)
tree<-recluster.cons(datamod,tr=10)
multiboot<-recluster.multi(tree$cons,tr=10,boot=50,datamod,levels=2,step=1)
recluster.plot(tree$cons,multiboot,1,2,direction="downwards")