kda.configure {Mergeomics} | R Documentation

## Set parameters for weighted key driver analysis (wKDA)

### Description

takes the configuration (plan) parameter for wKDA process as input and assigns default values if needed. The fields of this parameter are listed in the arguements section in detail.

### Usage

    kda.configure(plan)

### Arguments

`plan` | a parameter including fields about the details of the wKDA process:
    label:    unique identifier for the analysis
    folder:   parent folder for results
    netfile:  path to network file (TAIL HEAD WEIGHT)
    modfile:  path to module file (MODULE GENE)
    inffile:  path to module info file
    nodfile:  path to node selection file
    depthsearch: depth for subgraph search
    direction: 0 for undirected, negative for downstream and
    positive for upstream
    maxoverlap: maximum allowed overlap between two key driver
    neighborhoods
    minsize:  minimum module size
    mindegreeminimum: node degree to qualify as a hub
    maxdegreemaximum: node degree to include
    edgefactor: influence of node strengths: 0.0 no influence,
    1.0 full influence
    seed: seed for random number generator

### Details

`kda.configure` prepares the environment for wKDA process, checks the fields of the input plan parameter (that includes paths of required input files and output folder, min module size, etc.), and assigns the default values to these fields if they are not specified.

### Value

`plan` | configured and -if needed updated- plan parameter to be used in wKDA process.

### 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`

### Examples

    ## for KDA the essential parameters should be assigned by user is as follows:
    plan <- list()
    ## assign job label:
    plan$label<-"HDLC"
    ## specify parent folder for results:
    plan$folder<-"Results"
    ## Get an input network (columns: TAIL HEAD WEIGHT)
    plan$netfile <-"network.mouseliver.mouse.txt"
    ## Get the gene sets derived from ModuleMerge, containing two columns,
    ## MODULE and NODE, delimited by tab
    plan$modfile<- "moddata.txt"
    ## If above parameters are not assigned by users, code will stop with error:
    if(is.null(plan$folder)) stop("No parent folder.")
    if(is.null(plan$label)) stop("No job label.")
    if(is.null(plan$netfile)) stop("No network file.")
    if(is.null(plan$modfile)) stop("No module file.")

    ## other parameters are optional, if they are not specified by user,
    ## kda.configure assigns their default values:
    ## graph search depth parameter:
    if(is.null(plan$depth)) plan$depth <- 1
    ## edge directionality in the network: O means undirected
    if(is.null(plan$direction)) plan$direction <- 0
    ## max overlap allowed between two modules
    if(is.null(plan$maxoverlap)) plan$maxoverlap <- 0.33
    ## min size of the modules
    if(is.null(plan$minsize)) plan$minsize <- 20
    ## min and max hub degree to be included:
    if(is.null(plan$mindegree)) plan$mindegree <- "automatic"
    if(is.null(plan$maxdegree)) plan$maxdegree <- "automatic"
    ## number of simulations for permutation test:
    if(is.null(plan$nperm)) plan$nperm <- 2000
    ## seed for random number generator:
    if(is.null(plan$seed)) plan$seed <- 1
    ## these are the main parameters needed to be assigned default values.

[Package Mergeomics version 1.18.0 Index]