Consensus network is built from taking the average ranks of the edges in multiple network predictions.
average.consensus(adjmatrix.list, directed = F)
a list of inferred network matrices with same row and column ordering.
logical. If TRUE, the network is considered as directed. If FALSE, the upper triangular part of the symmetric matrix is used to calculate the rank matrix
average.consensus returns a network with rank average edge ranks. The weights are rescaled to 0-1 and hihger values indicate higher ranks.
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##create two random networks library(RLowPC) set.seed(4) net1<-abs(matrix(rnorm(16),4,4)) net1<-pmax(net1,t(net1)) diag(net1)<-0 set.seed(5) net2<-abs(matrix(rnorm(16),4,4)) net2<-pmax(net2,t(net2)) diag(net2)<-0 dimnames(net1)<-dimnames(net2)<-list(letters[1:4],letters[1:4]) net.list<-list(net1=net1,net2=net2) inf.consensus<-average.consensus(adjmatrix.list = net.list,directed = F) adj2rankadj(net1) adj2rankadj(net2) inf.consensus
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