Description Usage Arguments Details Value Author(s) References See Also Examples
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.
1 | kda.finish(job)
|
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. |
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.
job |
updated information including the overlapping hub neighborhoods, co-hubs information, top driver of each module, and their updated and sorted p-values. |
Ville-Petteri Makinen
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.
kda.finish.estimate
, kda.finish.save
,
kda.finish.summarize
, kda.finish.trim
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ## 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)
|
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