kda.finish.summarize: Summarize the wKDA results
In zeynebkurtUCLA/Mergeomics: Integrative network analysis of omics data

Description Usage Arguments Details Value Author(s) References See Also Examples

Create a summary file of top key drivers. The file includes the key driver of each block of the dataset and their p-values.

1	kda.finish.summarize(res, job)

`res`	the data frame including the p-values, false discovery rates, and fold scores of the nodes obtained from `kda.finish.trim`
`job`	the data frame including the path of output file which will briefly contain top key drivers of the blocks and ranked p-values of those top key drivers

kda.finish.summarize determines the ranking scores of blocks, finds the top node for each block, selects and saves top key drivers, and stores P-values into file. top drovers of the blocks are also returned to the user.

res

data frame including top node for each block

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

## get the prepared and KDA applied dataset:(see kda.analyze for details)
data(job_kda_analyze)
## finish the KDA process by estimating additional measures for the modules
## such as module sizes, overlaps with hub neighborhoods, etc.
# job.kda <- kda.finish(job.kda)
# if (nrow(job.kda$results)==0){
# cat("No Key Driver Found!!!!")
# } else{
##  Estimate additional measures - see kda.analyze and kda.finish for details
#   res <- kda.finish.estimate(job.kda)
##  Save full results about modules such as co-hub, nodes, P-values info etc.
#   res <- kda.finish.save(res, job.kda)
##  Create a simpler file for viewing by trimming floating numbers
#   res <- kda.finish.trim(res, job.kda)
##  Create a summary file of top hit KDs.
#   res <- kda.finish.summarize(res, job.kda)
# }
## See kda.analyze() and kda.finish() for details