Usage
## S3 method for class 'best':
plot(x,mystat="fldc",siglevel=0.05,sigtype=c("raw","corrected","fdr"),
partition=NA,print.num=TRUE,print.lab=TRUE,float=0.01,col.best=c(2,3),
cex.best=0.8,cex.leaf=0.8,font.best=NULL,main=NULL,sub=NULL,xlab=NULL,
metric.args=list(),...)
Arguments
x
An object of class best
, such as computed by the SigTree
function. mystat
A measure of tightness for which p-values are to be shown in the plot. Default is "fldc"
. Other options are "fldcc"
and "bldc"
.
siglevel
A threshold level of significance for tightness of branches used when partition=NA
. Default is 0.05. If the estimate of significance for a node is below threshold, it will be shown on the plot next to the node.
sigtype
A character string specifying how the significance threshold siglevel
should be interpreted. If "raw"
, the threshold will be applied directly to the p-values tabulated for each tree node in x
. With "corrected"<
print.num
Logical. If true, the branch numbers will be indicated.
print.lab
Logical. If true, the labels will be displayed at the bottom of dendrogram.
float
A numeric value that can change the vertical location of pvalues.
col.best
A character vector of length 2, indicating the colors to be used for the p-values and for the numbers of the nodes.
cex.best
A numeric value for the text size of the branch labels.
cex.leaf
A numeric value for the text size of the leaf labels.
font.best
An integer which specifies font choice of text on the plot. See ?par
function parameter font
for details.
main
A character string specifying the title of the plot.
sub
A character string specifying a subtitle of the plot.
xlab
A caracter string specifying the label of horizontal axis.
metric.args
Additional argument from user supplied dissimilariity(distance) function. See details
and examples
below for further explanation.
...
Further arguments to be passed on to the plot
function.
Examples
data(leukemia)
mytable<-SigTree(data.matrix(leukemia),mystat="all",
mymethod="ward",mymetric="euclidean",rand.fun="shuffle.column",
distrib="Rparallel",njobs=2,Ptail=TRUE,tailmethod="ML")
plot(x=mytable,mystat="fldc",siglevel=0.001,sigtype="raw",hang=-1)
mypartition<-PartitionTree(x=mytable,siglevel=0.001,statname="fldc",
sigtype="raw")
plot(x=mytable,mystat="fldc",partition=mypartition)
plot(x=mytable,mystat="fldc",partition=mypartition,print.num=F)
#with user-defined functions
mydist<-function(x,y){return(dist(x)/y)}
myrand<-function(x,z){return(apply(x+z,2,sample))}
mytable<-SigTree(data.matrix(leukemia),mystat="fldc",
mymethod="ward",mymetric="mydist",rand.fun="myrand",
distrib="Rparallel",njobs=2,Ptail=TRUE,tailmethod="MOM",metric.args=list(3),
rand.args=list(2))
plot(mytable,metric.args=list(3))
plot(mytable,metric.args=list(3),cex.leaf=1.5)