kda.finish.summarize {Mergeomics} | R Documentation

## Summarize the wKDA results

### Description

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

### Usage

    kda.finish.summarize(res, job)

### Arguments

`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

### Details

`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.

### Value

`res` | data frame including top node for each block

### 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.trim`

### 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)
    ##  Create a summary file of top hit KDs.
    #   res <- kda.finish.summarize(res, job.kda)
    # }
    ## See kda.analyze() and kda.finish() for details

[Package Mergeomics version 1.18.0 Index]