build_coexp_network {EGAD} | R Documentation

## 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

    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

    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)

[Package EGAD version 1.20.0 Index]