| epoc.bootstrap {epoc} | R Documentation |
epoc.bootstrap
Description
Bootstrap for the EPoC methods
Usage
epoc.bootstrap(Y, U, nboots=100, bthr=NULL, method='epocG',...)
## S3 method for class 'bootsize'
plot(x, lambda.boot=NULL, B, range=c(0,1), ...)
epoc.final(epocboot, bthr=0.2, k)
Arguments
Y |
mRNA, samples x genes. |
U |
CNA, samples x genes. |
nboots |
Number of bootstrap iterations to run. |
method |
For |
x |
A sparse network matrix or a list of the same, non-zeros are links. These come from e.g. |
lambda.boot |
The |
B |
Number of bootstrap iterations ran for |
range |
Range of bootstrap thresholds to display. |
epocboot |
For |
k |
For |
bthr |
Require presence of links in 100*bthr% of the bootstrap iterations. |
... |
Parameters passed down to an underlying function. For |
Details
epoc.bootstrap run epocA or epocG using bootstrap.
Value
epoc.bootstrap returns a list of p \times p arrays of values in [0,1] where 1 is presence of link in 100% of bootstrap iterations for the k different \lambda values for p different genes.
epoc.final returns a sparse matrix of p \times p values in [0,1] where 1 is presence of link in 100% of bootstrap iterations, but thresholded such that all values have be greater than or equal to bthr.
References
Rebecka Jörnsten, Tobias Abenius, Teresia Kling, Linnéa Schmidt, Erik Johansson, Torbjörn Nordling, Bodil Nordlander, Chris Sander, Peter Gennemark, Keiko Funa, Björn Nilsson, Linda Lindahl, Sven Nelander. (2011) Network modeling of the transcriptional effects of copy number aberrations in glioblastoma. Molecular Systems Biology 7 (to appear)
See Also
epoc, plot.EPoC.validation, plot.EPOCA, plot.EPOCG