run,RnBClusterRun-method {RnBeads} | R Documentation

## run-methods

### Description

Runs the analysis by submitting jobs for each module to the compute cluster

### Usage

    ## S4 method for signature 'RnBClusterRun'
    run(
      object,
      analysis.id,
      config.xml,
      split.differential = TRUE,
      dry.run = FALSE,
      long.cmd.thres = 1024L,
      queue = NULL
    )

### Arguments

`object` | `RnBClusterRun` object
`analysis.id` | analysis id. used for naming submitted jobs and log files
`config.xml` | XML file specifying the analysis options and parameter settings
`split.differential` | flag indicating whether to split the differnetial methylation module into seperate jobs according to sample annotation column and region type.
`dry.run` | Prevent the actual job submission. Rather only write to a shell script file
`long.cmd.thres` | commands that are longer than this number will be encapsulated in shell scripts rather than being submitted as direct command
`queue` | The name of the queue the jobs are going to be submitted to

### Value

Nothing of importance

### Author(s)

Fabian Mueller

### Examples

    #specify the xml file for your analysis
    xml.file <- "MY_ANALYSIS_SETTINGS.XML"
    #set the cluster architecture specific to your environment
    arch <- new("ClusterArchitectureSGE")
    rnb.cr <- new("RnBClusterRun",arch)
    #set up the cluster so that 32GB of memory are required (SGE resource is called "mem_free")
    rnb.cr <- setModuleResourceRequirements(rnb.cr,c(mem_free="32G"),"all")
    #set up the cluster to use 4 cores on each node for all modules
    rnb.cr <- setModuleNumCores(rnb.cr,4L,"all")
    #set up the cluster to use 2 cores for the exploratory analysis module
    rnb.cr <- setModuleNumCores(rnb.cr,2L,"exploratory")
    #run the actual analysis (remove dry.run=TRUE, to really submit the jobs)
    run(rnb.cr, "rnbeads_analysis", xml.file, dry.run=TRUE)

[Package RnBeads version 2.12.2 Index]