I'd like to use BioNet to identify high-scoring subnetworks in my data.
The tutorial clearly explains how to identify the top scoring subnetwork (I don't have the CPLEX library so I'm using
library(BioNet) library(DLBCL) data(dataLym) data(interactome) pvals <- cbind(t=dataLym$t.pval, s=dataLym$s.pval) rownames(pvals) <- dataLym$label pval <- aggrPvals(pvals, order=2, plot=FALSE) subnet <- subNetwork(dataLym$label, interactome) subnet <- rmSelfLoops(subnet) subnet A graphNEL graph with undirected edges Number of Nodes = 2559 Number of Edges = 7788 fb <- fitBumModel(pval, plot=FALSE) scores <- scoreNodes(subnet, fb, fdr=0.001) module <- runFastHeinz(subnet, scores) module A graphNEL graph with undirected edges Number of Nodes = 37 Number of Edges = 44
But what about other high-scoring subnetworks? It is likely that in a network with 2259 nodes there will be other interesting active subnetworks to explore other than the first one. How can I retrieve these?
Bonus question: are there any parameters that I can set to increase or decrease the size of the resulting subnetworks?