build_coexp_expressionSet: Builds a coexpression network from an expressionSet

In EGAD: Extending guilt by association by degree

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')

EGAD documentation built on Nov. 8, 2020, 8:31 p.m.