clusterInteractions-methods: Grouping DNA interactions by enrichment profile

In sirusb/R3CPET: 3CPET: Finding Co-factor Complexes in Chia-PET experiment using a Hierarchical Dirichlet Process

Description

This method aims at clustering the DNA interactions according to their partnership probability to the inferred chromatin maintainer networks.

Usage

## S4 method for signature 'ChromMaintainers'
clusterInteractions(object, method="sota", nbClus=20 )

Arguments

object	(Required) a non-empty ChromMaintainers object
method	(optional)used to specify the method to use. Only the method = "sota" is supported for the moment, the method='clues' is deprecated. The user needs to specify the number of clusters by setting the parameter nbClus, by default it is set to 20.
nbClus	(optional) The user-specified number of clusters. It is taken into consideration only if method = sota.

Value

A ChromMaintainers object in which the clusRes is populated as a sota.

Author(s)

Mohamed Nadhir Djekidel ([e-mail])

References

Herrero, J., Valencia, A, and Dopazo, J. (2005). A hierarchical unsupervised growing neural network for clustering gene expression patterns. Bioinformatics, 17, 126-136.

See Also

ChromMaintainers, sota, InferNetworks

Examples

 data(RPKMS)

  ## 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)
  x

  ## build networks connecting each interacting regions
  nets<- buildNetworks(x)

  ## infer the networks
  hlda<- InferNetworks(nets)

  #cluster
  hlda<- clusterInteractions(hlda)

  #Display heatmap
  plot3CPETRes(hlda,type="heatmap")
  hlda

## End(Not run)

sirusb/R3CPET documentation built on Oct. 12, 2020, 6 p.m.