Mergeomics (version 1.0.0)

kda.start.modules: Import module descriptions

Description

kda.start.modules searches the whole nodes of the modules within the nodes of edgdata edgelist, filters out the nodes that does not exist in the nodes of edgdata, and deletes the modules, which does not have enough nodes.

Usage

kda.start.modules(job, edgdata)

Arguments

job

a data frame including information such as module data file name, edge direction, minimum acceptable module size (job$modfile, job$direction, job$minsize, and so on.)

edgdata

edge list data obtained from kda.start.edges

Value

moddata

module descriptions and their member node lists

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, kda.prepare, kda.start

Examples

job.kda <- list()
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$direction <- 1
job.kda$nperm <- 20 # the default value is 2000, use 20 for unit tests
job.kda <- kda.configure(job.kda)

## Import topology of the graph for KDA, then find the module statistics
## This is already had been done in the kda.start() main function, due to
## the time constraint while running examples, we did not run it again.
# edgdata <- kda.start.edges(job.kda)
## Find module memberships of the graph nodes and obtain module statistics:
# moddata <- kda.start.modules(job.kda, edgdata)

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