R3CPET (version 1.4.2)

buildNetworks: Building interaction networks connecting interacting regions

Description

This methods uses the background PPI to try to build an interaction network that connects each interacting regions. If a regionA interacts with a regionB and if $TF_A$ is the list of TF in regionA and $TF_B$ is the list of TF in regionB, than we use the loaded PPI as a background network to connect each TF from $TF_A$ to each TF in $TF_B$. We suppose that a minimum number of physical interactions (minimum energy) are needed to connection each TF to the other. Thus, we take the shortest path in the PPI. at this stage, each network is a collection of edges.

Usage

"buildNetworks"(object, minFreq = 0.25, maxFreq = 0.75)

Arguments

object

a ChiapetExperimentData object in which the interactions and TFBS and PPI are already loaded. Check loadPETs, loadTFBS, loadPPI for more info.

minFreq

After constructing the networks for all the interacting regions all edges that appear in less than minFreq of the networks are considered to be outliers.

maxFreq

After constructing the networks for all the interacting regions all edges that appear in more than maxFreq of the networks are considered to be interactions involving general TF and are removed.

Value

A NetworkCollection object that contain the list of all the constructed networks and their sizes.NOTE: interactions for which no TF was bound or no networks could be constructed or which was empty after filtering will not be considered.

References

Mohamed Nadhir D, Yang C et al 3CPET: Finding Co-factor Complexes in Chia-PET experiment using a Hierarchical Dirichlet Process, ....

See Also

ChiapetExperimentData, loadTFBS , loadPETs, loadPPI, createIndexes

Examples

    
  ## get the different datasets path
  petFile <- file.path(system.file("example",package="R3CPET"),"HepG2_interactions.txt")  
  tfbsFile <- file.path(system.file("example",package="R3CPET"),"HepG2_TF.txt.gz")  
    
  
   ## Not run:   
#   x <- ChiapetExperimentData(pet = petFile, tfbs=  tfbsFile, IsBed = FALSE, ppiType="HPRD", filter= TRUE) 
#   ## build the diffrent indexes
#   x <- createIndexes(x)  
# 
#   ## build networks connecting each interacting regions
#   nets<- buildNetworks(x)
#   nets
# ## End(Not run)