kda2himmeli {Mergeomics} | R Documentation

## Generate input files for Himmeli

### Description

`kda2himmeli` generates input files for Himmeli 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

    kda2himmeli(job, modules = NULL, ndrivers = 5)

### Arguments

`job` | KDA result data list as returned by `kda.finish`
`modules` | array of module names to be visualized
`ndrivers` | maximum number of drivers per module

### Details

`kda2himmeli` first, selects top scoring key drivers for each module; then, assigns a colormap to modules, processes each module separately, finds key nodes' neighborhoods, and saves the edge and node lists of the modules to the specified output folder. Besides, it returns this configuration data to the user.

### Value

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

### Author(s)

Ville-Petteri Makinen

### 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$netfile<-system.file("extdata","network.mouseliver.mouse.txt",
    package="Mergeomics")
    job.kda$nodfile <- system.file("extdata","msea2kda.nodes.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 <- kda2himmeli(job.kda)

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

[Package Mergeomics version 1.15.0 Index]