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## __________________________________________________________
##
## BuildNetwork
##
## Given a list of scored edges and a REQUIRED vector of labels
## (e.g, 1:p), this function builds an object "Network".
##
## This is useful for exporting a network described by a list of
## edges to a network described by an adjacency matrix.
##
##
## INPUT
## - Edges : a n x 3 matrix (each line contains a couple of
## vertices plus the associated score)
## - Labels : a vector
## - nonedges.val : optional. Value attributed to the not existing
## edges in the generated score matrix out\$Score, default=NA.
##
## OUTPUT
## - Network : a list that contains the number of vertices, a
## vector of labels of the vertices, a vector of the connected
## vertices, the proportion of edges, the number of edges, the
## graph of the network (an adjacency matrix and a list of edges)
## and a valued matrix for the edges.
## __________________________________________________________
##
BuildNetwork <- function(Edges,Labels,nonedges.val=NA){
## initialize
Net = list()
Net$Vertices = list()
Net$Edges = list()
## vertices (genes)
Net$Vertices$Num <- length(Labels)
Net$Vertices$Labels <- Labels
## proportion and number of edges
Net$Edges$Prop <- length(Edges[,1])/(length(Labels)^2)
Net$Edges$Num <- dim(Edges)[1]
## matrix of edges (plus the associated weight)
Net$Edges$List <- Edges
## indicates the "connected" genes of the network
Net$Vertices$Connected <- which(Labels %in% Net$Edges$List[,1:2])
## Build the adjacency Matrix
Net$AdjMatrix <- matrix(0,Net$Vertices$Num,Net$Vertices$Num)
for (k in 1:Net$Edges$Num) {
Net$AdjMatrix[which(Labels == Net$Edges$List[k,2]),which(Labels == Net$Edges$List[k,1])] <- 1
}
## Build the matrix of edge values Matrix
Net$Score <- matrix(nonedges.val,Net$Vertices$Num,Net$Vertices$Num)
for (k in 1:Net$Edges$Num) {
Net$Score[which(Labels == Net$Edges$List[k,2]),which(Labels == Net$Edges$List[k,1])] <- Edges[k,3]
}
return(Net)
}
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