kda.start.modules {Mergeomics} | R Documentation

## Import module descriptions

### Description

`kda.start.modules` searches the whole nodes of the modules within the nodes of `edgdata` edgelist, filters out the nodes that does not exist in the nodes of `edgdata`, and deletes the modules, which does not have enough nodes.

### Usage

    kda.start.modules(job, edgdata)

### Arguments

`job` | a data frame including information such as module data file name, edge direction, minimum acceptable module size (`job$modfile`, `job$direction`, `job$minsize`, and so on.)
`edgdata` | edge list data obtained from `kda.start.edges`

### Value

`moddata` | module descriptions and their member node lists

### 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`

### 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
    job.kda <- kda.configure(job.kda)

    ## Import topology of the graph for KDA, then find the module statistics
    ## This is already had been done in the kda.start() main function, due to
    ## the time constraint while running examples, we did not run it again.
    # edgdata <- kda.start.edges(job.kda)
    ## Find module memberships of the graph nodes and obtain module statistics:
    # moddata <- kda.start.modules(job.kda, edgdata)

    ## remove the results folder
    unlink("Results", recursive = TRUE)

[Package Mergeomics version 1.18.0 Index]