ISA-Biclust conversion {eisa} | R Documentation |
The biclust package implements several biclustering
algorithms in a unified framework. The result of the biclustering is a
Biclust
object. These functions allow the
conversion between Biclust
and
ISAModules
objects.
To convert an ISAModules
object (mods
) to a
Biclust
object (bc
), you can do:
bc <- as(mods, "Biclust")The seed data and run data of the
ISAModules
object is stored
in the Parameters
slot of the Biclust
object. The ISA
scores are binarized by the conversion.
To convert a Biclust
object (bc
) to an ISAModules
object (mods
), you can call:
mods <- as(bc, "ISAModules")The
Parameters
slot of the Biclust
object is used as the
run data of the ISAModules
object. The seed data of the new
object will be an empty data frame.
Gabor Csardi Gabor.Csardi@unil.ch
Bergmann S, Ihmels J, Barkai N: Iterative signature algorithm for the analysis of large-scale gene expression data Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Mar;67(3 Pt 1):031902. Epub 2003 Mar 11.
Sebastian Kaiser, Rodrigo Santamaria, Roberto Theron, Luis Quintales and Friedrich Leisch. (2009). biclust: BiCluster Algorithms. R package version 0.8.1. http://CRAN.R-project.org/package=biclust
if (require(biclust)) { library(ALL) data(ALL) ALL.filtered <- ALL[sample(1:nrow(ALL), 1000),] # Biclust -> ISAModules set.seed(1) Bc <- biclust(exprs(ALL.filtered), BCPlaid(), fit.model = ~m + a + b, verbose = FALSE) Bc@Parameters$annotation <- annotation(ALL) modules <- as(Bc, "ISAModules") Bc modules getNoFeatures(modules) getNoSamples(modules) # ISAModules -> Biclust data(ALLModulesSmall) Bc2 <- as(ALLModulesSmall, "Biclust") ALLModulesSmall getNoFeatures(ALLModulesSmall) getNoSamples(ALLModulesSmall) Bc2 }