build_coexp_expressionSet: 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

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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

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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_expressionSet(exprs, gene.list, method='pearson')

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