\name{get.subnets} \alias{get.subnets} \title{get.subnets} \description{ List the detected subnetworks (each is a list of nodes in that subnetwork). } \usage{ subnets <- get.subnets(model, level = NULL, get.names = TRUE, stat = NULL, min.size = NULL, max.size = NULL, min.responses = NULL) } \arguments{ \item{model}{Output from the detect.responses function. An object of NetResponseModel class.} \item{level}{ Agglomeration level to investigate. The agglomerative algorithm grows the subnetworks step-by-step. This option can be used to select a particular step during the learning process. Will be included in the next version. } \item{get.names}{Logical. Indicate whether to return subnetwork nodes using node names (TRUE) or node indices (FALSE).} \item{stat}{Subnetwork summary statistics. If this is not readily provided through this option (i.e. stat = NULL), it will be calculated. Can speed up the get.subnets function.} \item{min.size, max.size }{Numeric. Filter out subnetworks whose size is not within the limits specified here.} \item{min.responses }{Numeric. Filter out subnetworks with less responses (mixture components) than specified here.} } \value{ A list of subnetworks.} \references{Leo Lahti et al.: Global modeling of transcriptional responses in interaction networks. Bioinformatics (2010).} \author{Leo Lahti } \examples{ library(netresponse) # Load a pre-calculated netresponse model obtained with # model <- detect.responses(toydata$emat, toydata$netw, verbose = FALSE) data( toydata ) model <- toydata$model #List the detected subnetworks #(each is a list of nodes for the given subnetwork): get.subnets(model) } \keyword{utilities}