Mergeomics (version 1.0.0)

kda.finish: Organize and save results

Description

After wKDA process is accomplished, kda.finish.estimate sums up the results and log them to the relevant files and folders. Besides, return them within the given job parameter.

Usage

kda.finish(job)

Arguments

job

the data list including label and folder fields to specify a unique identifier for the wKDA process and the output folder for the obtained results, respectively.

Value

job

updated information including the overlapping hub neighborhoods, co-hubs information, top driver of each module, and their updated and sorted p-values.

Details

kda.finish.estimate estimates additional measures if needed, saves results into relevant files, trims numbers to provide a simpler file for viewing, and stores a summary file of top hits after the wKDA prcess is accomplished. It also obtains the overlaps of the modules with hub neighborhoods, finds co-hubs information, determines the top key driver for each module and saves the updated and sorted p-values belonging to them.

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.finish.estimate, kda.finish.save, kda.finish.summarize, kda.finish.trim

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)

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