bootstrap {Oncotree} | R Documentation |
Bootstrap an oncogenetic tree to assess stability
Description
bootstrap.oncotree
provides a set of resampling
based estimates of the oncogenetic tree. Both a parametric and
non-parametric approach is available. The print
and
plot
methods provide interfaces for printing a summary and
plotting the resulting set of trees.
Usage
bootstrap.oncotree(otree, R, type = c("nonparametric", "parametric"))
## S3 method for class 'boottree'
print(x, ...)
## S3 method for class 'boottree'
plot(x, minfreq=NULL, minprop=NULL, nboots=NULL, draw.orig=TRUE,
draw.consensus=TRUE, fix.nodes=FALSE,
ask=(prod(par("mfrow"))<ntrees)&&dev.interactive(), ...)
Arguments
otree |
An object of class |
R |
The number of bootstrap replicates. |
type |
The type of bootstrap - see Details for explanations. |
x |
An object of class |
minfreq |
A lower limit on the occurrence frequency of the tree in “boottree” for plotting. By default, all unique trees are plotted, which can lead to a large number of plots. |
minprop |
A lower limit on the occurrence proportion of the tree in “boottree” for plotting. |
nboots |
A lower limit on the number of bootstrapped trees plotted. |
draw.orig |
logical; if TRUE the original tree is plotted. |
draw.consensus |
logical; if TRUE the consensus tree is plotted (see Details). |
fix.nodes |
logical; if TRUE, the nodes for all trees are kept in the same position. If |
ask |
logical; if TRUE, the user is asked before each plot, see |
... |
Ignored for |
Details
Parametric bootstrap: This approach assumes that the model is correct. Based on otree
, a random data set is generated R times using generate.data
. An oncogenetic tree is fitted to each of these random data sets.
Non-parametric bootstrap: The samples (rows) from the data associated with the tree are resampled with replacement R times, each time obtaining a data set with the same sample size. An oncogenetic tree is fitted to each of these resampled data sets.
For both approaches, a consensus tree that assigns to each vertex the parent that occurs most frequently in the bootstrapped trees, is also computed.
Value
For bootstrap.oncotree
: an object of class boottree
with the following components:
original |
The |
consensus |
A numeric vector with the |
parent.freq |
A matrix giving the number of trees with each possible child-parent edge. The rows correspond to children while the column to parents. |
tree.list |
A data frame with each row representing a unique tree obtained during the bootstrap. The ‘Tree’ variable contains the |
type |
A character value with the type of the bootstrap performed. |
For print.boottree
:
the original object is returned invisibly. It prints a summary showing the number of replicates, the number of unique trees found, and the number of times that the original tree was obtained.
For plot.oncotree
:
nothing is returned. It is used for its side effect of producing a sequence of plots of the bootstrapped trees. Specifically, it plots the original tree (if draw.orig=TRUE
), the consensus tree (if draw.consensus=TRUE
), and then the other trees by frequency of occurrence. To limit the number of bootstrapped trees plotted, specify exactly one of minfreq
, minprop
or nboots
. By default, if the session is interactive, the user is asked for confirmation before each new tree is drawn. To avoid this, either use ask=FALSE
in the function call, or set up a layout that fits all the trees.
Author(s)
Lisa Pappas, Aniko Szabo
See Also
Examples
data(ov.cgh)
ov.tree <- oncotree.fit(ov.cgh[1:5])
set.seed(43636)
ov.b1 <- bootstrap.oncotree(ov.tree, R=100, type="parametric")
ov.b1
opar <- par(mfrow=c(3,2), mar=c(2,0,0,0))
plot(ov.b1, nboots=4)
plot(ov.b1, nboots=4, fix.nodes=TRUE)
par(opar)