Builds a coexpression network from an expressionSet

Description

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.

Usage

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build_coexp_network(exprs, gene.list, method = "spearman", flag = "rank")

Arguments

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

Value

net Matrix symmetric

Examples

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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)

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