ARTIVA (version 1.2.3)

geneNetworkSummary: Function to

Description

This function is used for printing a summary of the gene network estimated with the ARTIVA procedure (ARTIVAnet, ARTIVAsubnet) for Auto Regressive TIme-VArying network inference.

Usage

geneNetworkSummary(ARTIVAnet, edgesThreshold)

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.

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)
# 
# # Print a summary of the obtained network 
# geneNetworkSummary(ARTIVAtest$network, edgesThreshold = 0.3)
# 
# # List of target genes to be analyzed independantly with ARTIVA
# targetGenes = c("TF3", 45, 50)
# ARTIVAtest2 = ARTIVAnet(targetData = simulatedProfiles[targetGenes,],
#   parentData = simulatedProfiles[parentGenes,],
#   targetName = targetGenes,
#   parentNames = parentGenes,
#   segMinLength = 2,
#   edgesThreshold = 0.6, 
#   niter= 2000,
#   savePictures=FALSE)
# 
# # Print a summary of the obtained network 
# geneNetworkSummary(ARTIVAtest2, edgesThreshold = 0.3)
# 
# # Re-compute a time-varying network from the output of function 
# # ARTIVAsubnet with new analysis parameters
# analysis2 = ARTIVAsubnetAnalysis(ARTIVAsubnet=ARTIVAtest,
#   segMinLength = 3,
#   edgesThreshold = 0.5,
#   outputPath="ARTIVAsubnet2",
#   savePictures=FALSE)
# 
# # Print a summary of the network obtained with the 2nd analysis.
# geneNetworkSummary(analysis2$network, edgesThreshold = 0.3)
# ## End(Not run)