visTreeBSclust: Function to obtain clusters from a bootstrapped tree

Description Usage Arguments Value Note See Also Examples

View source: R/visTreeBSclust.r

Description

visTreeBSclust is supposed to obtain clusters from a bootstrapped tree.

Usage

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
visTreeBSclust(
tree_bs,
bootstrap.cutoff = 80,
max.fraction = 1,
min.size = 3,
visTree = TRUE,
plot.phylo.arg = NULL,
nodelabels.arg = NULL,
verbose = TRUE,
...
)

Arguments

tree_bs

an "phylo" object storing a bootstrapped tree

bootstrap.cutoff

an integer specifying bootstrap-derived clusters

max.fraction

the maximum fraction of leaves contained in a cluster

min.size

the minumum number of leaves contained in a cluster

visTree

logical to indicate whether the tree will be visualised. By default, it sets to true for display

plot.phylo.arg

a list of main parameters used in the function "ape::plot.phylo" http://rdrr.io/cran/ape/man/plot.phylo.html. See 'Note' below for details on the parameters

nodelabels.arg

a list of main parameters used in the function "ape::nodelabels" http://rdrr.io/cran/ape/man/nodelabels.html. See 'Note' below for details on the parameters

verbose

logical to indicate whether the messages will be displayed in the screen. By default, it sets to true for display

...

additional "ape::plot.phylo" parameters

Value

a data frame following components:

Note

A list of main parameters used in the function "ape::plot.phylo":

A list of main parameters used in the function "ape::nodelabels":

See Also

visTreeBootstrap

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
# 1) generate an iid normal random matrix of 100x10 
data <- matrix( rnorm(100*10,mean=0,sd=1), nrow=100, ncol=10)
colnames(data) <- paste(rep('S',10), seq(1:10), sep="")
data <- t(data)

# 2) build neighbor-joining tree with bootstrap values and visualise it by default
tree_bs <- visTreeBootstrap(data)

# 3) obtain clusters from a bootstrapped tree
res <- visTreeBSclust(tree_bs, bootstrap.cutoff=80)
## hide tip labels and modify the font of internal node labels
res <- visTreeBSclust(tree_bs, bootstrap.cutoff=80,
nodelabels.arg=list(cex=0.4), show.tip.label=FALSE)

supraHex documentation built on Nov. 26, 2020, 2:01 a.m.