kda.finish.trim: Trim numbers before save

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

View source: R/cle.LS.R

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

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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

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## 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.