export_network: Export networks as a CSV table.

In FrankD/nethet: A bioconductor package for high-dimensional exploration of biological network heterogeneity

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.

Author(s)

Frank Dondelinger

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]]

## Not run: 
# Save network in CSV format suitable for Cytoscape import
export_network(mixglasso.clustering, file='nethet_network.csv',
						 p.corrs.thresh=0.25, quote=FALSE)

## End(Not run)

FrankD/nethet documentation built on Oct. 5, 2020, 8:22 a.m.