kda.start {Mergeomics} | R Documentation

## Import data for weighted key driver analysis

### Description

`kda.start` converts identities (such as module descriptions, module identifiers, and module nodes) to indices. It prepares graph topology and module information for wKDA process.

### Usage

    kda.start(job)

### Arguments

`job` | a data frame including fields for edges and nodes information of the graph (TAIL, HEAD, WEIGHT). It also involves path of input files including module descriptions and module-gene lists.

### Details

`kda.start` imports graph and relevant module descriptor input files, creates an indexed graph structure, and converts identities to indices from module descriptions and module-gene lists. Hence, it concludes with a graph structure and a module set involving member gene IDs for each module.

### Value

`job` | Updated data frame including indexed graph topology, modules, and nodes information:
    graph:     indexed topology
    modules:   module identities
    modinfo:   module descriptions (indexed)
    moddata:   module data (indexed)
    module2nodes:  lists of node indices for each module
    modulesizes:   module sizes

### 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.analyze`, `kda.finish`, `kda.prepare`, `kda.start.edges`, `kda.start.identify`, `kda.start.modules`

### Examples

    job.kda <- list()
    job.kda$label<-"HDLC"
    ## parent folder for results
    job.kda$folder<-"Results"
    ## Input a network
    ## columns: TAIL HEAD WEIGHT
    job.kda$netfile<-system.file("extdata","network.mouseliver.mouse.txt",
    package="Mergeomics")
    ## Gene sets derived from ModuleMerge, containing two columns, MODULE,
    ## NODE, delimited by tab
    job.kda$modfile<- system.file("extdata","mergedModules.txt",
    package="Mergeomics")
    ## "0" means we do not consider edge weights while 1 is opposite.
    job.kda$edgefactor<-0.0
    ## The searching depth for the KDA
    job.kda$depth<-1
    ## 0 means we do not consider the directions of the regulatory interactions
    ## while 1 is opposite.
    job.kda$direction <- 1
    job.kda$nperm <- 20 # the default value is 2000, use 20 for unit tests

    ## kda.start() process takes long time while seeking hubs in the given net
    ## Here, we used a very small subset of the module list (1st 10 mods
    ## from the original module file):
    moddata <- tool.read(job.kda$modfile)
    mod.names <- unique(moddata$MODULE)[1:min(length(unique(moddata$MODULE)),
    10)]
    moddata <- moddata[which(!is.na(match(moddata$MODULE, mod.names))),]
    ## save this to a temporary file and set its path as new job.kda$modfile:
    tool.save(moddata, "subsetof.supersets.txt")
    job.kda$modfile <- "subsetof.supersets.txt"

    job.kda <- kda.configure(job.kda)
    ## Import data for weighted key driver analysis:
    job.kda <- kda.start(job.kda)

    ## Remove the temporary files used for the test:
    file.remove("subsetof.supersets.txt")
    ## remove the results folder
    unlink("Results", recursive = TRUE)

[Package Mergeomics version 1.22.0 Index]