kda2cytoscape {Mergeomics} | R Documentation

## Generate input files for Cytoscape

### Description

`kda2cytoscape` generates input files for Cytoscape to visualize the graph and hubnets after the wKDA process finished. The network visualization is a streamlined depiction of the module enrichment in hub neighborhoods.

### Usage

    kda2cytoscape(job, node.list = NULL, modules = NULL, ndrivers = 5,
    depth = 1)

### Arguments

`job` | wKDA result data list as returned by `kda.finish`
`node.list` | array of node/gene names to be visualized with their neighbor node. if this is not specified top `ndrivers` of each module and their neighborhoods will be illustrated.
`modules` | array of module names to be visualized
`ndrivers` | maximum number of drivers per module
`depth` | depth for neighborhood search in the graph

### Details

`kda2cytoscape` first, selects top scoring key drivers for each module; then, assigns a colormap to modules, processes each module separately, finds key nodes' neighborhoods within a particular search depth, and saves the edge and node lists of the modules to the specified output folder. Besides, it returns this configuration data to the user. Created file list for Cytoscape are given below:

    kda2cytoscape.top.kds.txt: top key drivers of the modules are
    listed in this file. Number of the key drivers can be set by
    user with ndrivers parameter.
    kda2cytoscape.edges.txt: edge lists of the integrated graph
    that includes the subnetworks of all modules.
    kda2cytoscape.nodes.txt: node lists of the integrated graph
    that includes the subnetworks of all modules.
    module.color.mapping.txt: color mapping for the  modules,
    i.e. one color is assigned to each module.

### Value

`job` | updated data list including the node and edge information of the modules converted to Cytoscape format

### Author(s)

Zeyneb Kurt

### References

Shu L, Zhao Y, Kurt Z, Byars SG, Tukiainen T, Kettunen J, Orozco LD, Pellegrini M, Lusis AJ, Ripatti S, Zhang B, Inouye M, Makinen V-P, Yang X. Mergeomics: multidimensional data integration to identify pathogenic perturbations to biological systems. BMC genomics. 2016;17(1):874.

### See Also

`kda.analyze`, `kda.finish`

### Examples

    ## get the prepared and KDA applied dataset:(see kda.analyze for details)
    data(job_kda_analyze)
    ## set the relevant parameters:
    job.kda$label<-"HDLC"
    ## parent folder for results
    job.kda$folder<-"Results"
    ## Input a network
    ## columns: TAIL HEAD WEIGHT
    job.kda$netfile<-system.file("extdata","network.mouseliver.mouse.txt",
    package="Mergeomics")
    ## Gene sets derived from ModuleMerge, containing two columns, MODULE,
    ## NODE, delimited by tab
    job.kda$modfile<- system.file("extdata","mergedModules.txt",
    package="Mergeomics")
    ## "0" means we do not consider edge weights while 1 is opposite.
    job.kda$edgefactor<-0.0
    ## The searching depth for the KDA
    job.kda$depth<-1
    ## 0 means we do not consider the directions of the regulatory interactions
    ## while 1 is opposite.
    job.kda$direction <- 1

    ## finish the KDA process
    job.kda <- kda.finish(job.kda)

    ## prepare the cytoscape-ready files:
    job.kda <- kda2cytoscape(job.kda)

    ## remove the results folder
    unlink("Results", recursive = TRUE)

[Package Mergeomics version 1.18.0 Index]