kda.finish.trim: Trim numbers before save

In zeynebkurtUCLA/Mergeomics: Integrative network analysis of omics data

Description

kda.finish.trim trims p-values, false discovery rates, and fold scores to make them nicer to look at before saving the file. It also returns trimmed results to the user.

Usage

kda.finish.trim(res, job)

Arguments

res	includes p-values, false discovery rates, and fold scores of the nodes
job	data frame including output folder path to store trimmed results

Value

res	Trimmed and formatted p-values, false discovery rates, and fold scores of the nodes

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

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

Examples

## 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)
# }
## See kda.analyze() and kda.finish() for details

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