nethet (version 1.4.2)

export_network: Export networks as a CSV table.

Description

This function takes the output of het_cv_glasso or mixglasso and exports it as a text table in CSV format, where each entry in the table records an edge in one group and its partial correlation.

Usage

export_network(net.clustering, file = "network_table.csv",
  node.names = rownames(net.clustering$Mu),
  group.names = sort(unique(net.clustering$comp)), p.corrs.thresh = 0.2,
  ...)

Arguments

net.clustering

A network clustering object as returned by screen_cv.glasso or mixglasso.

file

Filename to save the network table under.

node.names

Names for the nodes in the network. If NULL, names from net.clustering will be used.

group.names

Names for the clusters or groups. If NULL, names from net.clustering will be used (by default these are integets 1:numClusters).

p.corrs.thresh

Threshold applied to the absolute partial correlations. Edges that are below the threshold in all of the groups are not exported. Using a negative value will export all possible edges (including those with zero partial correlation).

...

Further parameters passed to write.csv.

Value

• Function does not return anything.

Examples

n = 500
p = 10
s = 0.9
n.comp = 3

# Create different mean vectors
Mu = matrix(0,p,n.comp)

# Define non-zero means in each group (non-overlapping)
nonzero.mean = split(sample(1:p),rep(1:n.comp,length=p))

# Set non-zero means to fixed value
for(k in 1:n.comp){
	Mu[nonzero.mean[[k]],k] = -2/sqrt(ceiling(p/n.comp))
}

# Generate data
sim.result = sim_mix_networks(n, p, n.comp, s, Mu=Mu)
mixglasso.result = mixglasso(sim.result$data, n.comp=3)
mixglasso.clustering = mixglasso.result$models[[mixglasso.result$bic.opt]]

# Save network in CSV format suitable for Cytoscape import
export_network(mixglasso.clustering, file='nethet_network.csv',
							 p.corrs.thresh=0.25, quote=FALSE)