kda2himmeli.drivers: Select top key drivers for each module

In zeynebkurtUCLA/Mergeomics: Integrative network analysis of omics data

Description

kda2himmeli.drivers finds maximally top ndriv key drivers for each module with respect to the significance level of the drivers.

Usage

kda2himmeli.drivers(data, modules, ndriv)

Arguments

data	data frame including information of the modules (key driver list, p-values, node list, false discovery rates (fdr), and so on.)
modules	top scoring modules among KDA results
ndriv	maximum number of drivers that can be chosen for per module

Value

data	top key drivers (maximally ndriv drivers for each module) for top modules (if module significance levels are given)

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

kda2himmeli

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")
job.kda$nodfile <- system.file("extdata","msea2kda.nodes.txt", 
package="Mergeomics")
## "0" means we do not consider edge weights while 1 is opposite.
job.kda$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)
## Select top key drivers from each module.
## First, take module names from kda results
modules <- unique(job.kda$results$MODULE)
## Take top 2 KDs:
drivers <- kda2himmeli.drivers(job.kda$results, modules, ndriv=2)

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

zeynebkurtUCLA/Mergeomics documentation built on May 14, 2019, 1:59 a.m.