| build_coexp_network {EGAD} | R Documentation |
The function generates a dense coexpression network from expression data stored as a
matrix, with the genes as row labels, and samples as column labels.
Correlation coefficicents are used as to weight the edges of the nodes (genes).
Calls cor.
build_coexp_network(exprs, gene.list, method = "spearman", flag = "rank")
exprs |
matrix of expression data |
gene.list |
array of gene labels |
method |
correlation method to use, default Spearman's rho |
flag |
string to indicate if the network should be ranked |
net Matrix symmetric
exprs <- matrix( rnorm(1000), ncol=10,byrow=TRUE)
gene.list <- paste('gene',1:100, sep='')
sample.list <- paste('sample',1:10, sep='')
rownames(exprs) <- gene.list
colnames(exprs) <- sample.list
network <- build_coexp_network(exprs, gene.list)