build_coexp_expressionSet {EGAD} | R Documentation

## Builds a coexpression network from an expressionSet

### Description

The function generates a dense coexpression network from expression data stored in the expressionSet data type. Correlation coefficicents are used as to weight the edges of the nodes (genes). Calls `build_coexp_network`.

### Usage

    build_coexp_expressionSet(exprsSet, gene.list, method = "spearman",
      flag = "rank")

### Arguments

`exprsSet` | data class ExpressionSet
`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_expressionSet(exprs, gene.list, method='pearson')

[Package EGAD version 1.10.0 Index]