Mergeomics (version 1.0.0)

kda.finish.trim: Trim numbers before save

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

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.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