isa.biclust | R Documentation |
This function converts the object with ISA modules to a Biclust
object, so all the functions in the biclust
package can be used
on it.
isa.biclust(modules)
modules |
The ISA modules, as returned by the |
biclust
is an R package that implements many biclustering
algorithms in a unified framework. This function converts a set of ISA
biclusters to a Biclust
object, this class is used to store all
biclustering results by the biclust
package.
The Biclust
class only supports binary biclusters, so the ISA
modules are binarized during the conversion.
A Biclust
object.
Gabor Csardi Gabor.Csardi@unil.ch
## You need the biclust package for this ## Not run: if (require(biclust)) { set.seed(1) data <- isa.in.silico() modules <- isa(data[[1]]) bc <- isa.biclust(modules) ## A heatmap drawHeatmap(data[[1]], bc, 1) ## A "bubble" plot bubbleplot(data[[1]], bc) ## Compare values inside and outside the bicluster plotclust(bc, data[[1]]) ## Plot profiles of bicluster elements parallelCoordinates(data[[1]], bc, number=1) ## Coherence measures vs. ISA robustness cV <- sapply(seq(bc@Number), function(x) constantVariance(data[[1]], bc, x, dimension="both")) aV <- sapply(seq(bc@Number), function(x) additiveVariance(data[[1]], bc, x, dimension="both")) mV <- sapply(seq(bc@Number), function(x) multiplicativeVariance(data[[1]], bc, x, dimension="both")) sV <- sapply(seq(bc@Number), function(x) signVariance(data[[1]], bc, x, dimension="both")) rob <- robustness(isa.normalize(data[[1]]), modules$rows, modules$columns) cor( cbind(cV, aV, mV, sV, rob) ) } ## End(Not run)
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