clusterInteractions-methods {R3CPET} | R Documentation

## Grouping DNA interactions by enrichment profile

### Description

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

Two kinds of clustering are supported supervised and un-supervised. In the first one the function`sota` from the `clValid` package. In the second case the `clues` method from the `clues` package is used.

### Usage

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

### Arguments

`object` | (Required) a non-empty `ChromMaintainers` object
`method` | (optional)used to specify the method to use. if `clues` is specified, the number of clusters will be determined automatically. if `method = "sota"` , the user can specify the number of clusters by setting the parameter `nbClus`, by default it is set to 20. by default `method = "clues"`. Another option is that user can first do an automatic clustering using `"clues"` and then if judges that more or less clusters are required he can recall the `clusterInteractions` method and specify the number the number of clusters.
`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` or `clues` object.

### Author(s)

Mohamed Nadhir Djekidel (nde12@mails.tsinghua.edu.cn)

### References

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

Wang, S., Qiu, W., and Zamar, R. H. (2007). CLUES: A non-parametric clustering method based on local shrinking. Computational Statistics & Data Analysis, Vol. 52, issue 1, pages 286-298

### See Also

`ChromMaintainers`, `clues` , `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)

[Package R3CPET version 1.18.0 Index]