ARTIVA (version 1.2.3)

traceNetworks: Function to plot the network estimated with functions ARTIVAnet or ARTIVAsubnet

Description

This function is used for plotting the network estimated with the ARTIVA procedure (ARTIVAnet, ARTIVAsubnet) and ARTIVAsubnetAnalysis for Auto Regressive TIme-VArying network inference.

Usage

traceNetworks(ARTIVAnet, edgesThreshold, parentColor = "blue",
targetColor = "grey", parentgeneNames = TRUE, targetgeneNames = TRUE,
layout = "fruchterman.reingold", onepage=TRUE)

Arguments

ARTIVAnet

Table containing the information to plot a time-varying regulatory network. In particular, this table can be obtained with function ARTIVAsubnet,

ARTIVAsubnetAnalysis (output value network) or ARTIVAnet (unique output value). Each row of the table describes one edge. The columns, entitled Target, CPini, CPfinal, Parent, PostProb, describe the name of the target gene, the changepoints defining the start and the end of the regulation, the parent name and the estimated posterior probability of the edge.

edgesThreshold

Probability threshold for the selection of the edges to be plotted.

parentColor

Color for plotting the node representing parent genes (optional, default: parentColor= "blue").

targetColor

Color for plotting the node representing target genes (optional, default: targetColor= "grey").

parentgeneNames

Boolean, if TRUE the name of the parent gene is plotted (optional, default: geneNames = TRUE).

targetgeneNames

Boolean, if TRUE the name of the target gene is plotted (optional, default: geneNames = TRUE).

layout

Name of the function determining the placement of the vertices for drawing a graph, possible values among others: "fruchterman.reingold", "geneLines",

"random", "circle", "sphere", "kamada.kawai","spring", "reingold.tilford", "fruchterman.reingold.grid", see package igraph0 for more details (default: layout="fruchterman.reingold").

onepage

Boolean, if TRUE, all output pictures are plotted on one page only (optional, default: onepage=TRUE.

Value

NULL

References

Statistical inference of the time-varying structure of gene-regulation networks S. Lebre, J. Becq, F. Devaux, M. P. H. Stumpf, G. Lelandais, BMC Systems Biology, 4:130, 2010.

See Also

ARTIVAnet,ARTIVAsubnet, ARTIVAsubnetAnalysis, CP.postDist,

segmentModel.postDist, plotCP.postDist

Examples

# Load the ARTIVA R package
library(ARTIVA)

# Load the dataset with simulated gene expression profiles
data(simulatedProfiles)

# Name of the target gene to be analyzed with ARTIVA 
targetGene = 1

# Names of the parent genes (typically transcription factors) 
parentGenes = c("TF1", "TF2", "TF3", "TF4", "TF5")


# Run the ARTIVAsubnet function
# Note that the number of iterations in the RJ-MCMC sampling is reduced 
# to 'niter=20000' in this example, but it should be increased (e.g. up to
# 50000) for a better estimation.

## Not run: 
# ARTIVAtest = ARTIVAsubnet(targetData = simulatedProfiles[targetGene,],
#   parentData = simulatedProfiles[parentGenes,],
#   targetName = targetGene,
#   parentNames = parentGenes,
#   segMinLength = 2,
#   edgesThreshold = 0.6, 
#   niter= 2000,
#   savePictures=FALSE)
# 
# # Re-compute a time-varying network from the output of function 
# # ARTIVAsubnet with new analysis parameters
# analysis2 = ARTIVAsubnetAnalysis(ARTIVAsubnet=ARTIVAtest,
#   segMinLength = 3,
#   edgesThreshold = 0.5,
#   outputPath="ARTIVAsubnet2",
#   savePictures=FALSE)
# 
# # Trace the obtained network.
# traceNetworks(analysis2$network, edgesThreshold = 0.3)
# ## End(Not run)