Mergeomics (version 1.0.0)

kda2himmeli: 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

Value

job

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

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.

References

Shu L, Zhao Y, Kurt Z, Byars S, Tukiainen T, Kettunen J, Ripatti S, Zhang B, Inouye M, Makinen VP, Yang X. Mergeomics: integration of diverse genomics resources to identify pathogenic perturbations to biological systems. bioRxiv doi: http://dx.doi.org/10.1101/036012

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)