Plot a pipeline workflow from a CytoPipeline run

Usage

plotSelectedWorkflow(experimentName, whichQueue, sampleFile, path = path)

Arguments

experimentName

the experiment name (representing a pipeline run) from which to extract the workflow

whichQueue

"pre-processing" or "scale transform"

sampleFile

in case 'whichQueue' is set to 'pre-processing, which sample file to look at. This can be a number or a character.

if whichQueue == "scale transform", the sampleFile is ignored
if NULL and whichQueue == "pre-processing", the sampleFile is defaulted to the first one belonging to the experiment

path

the root path to look for the CytoPipeline experiment cache

Value

nothing, but displays the plot as a side effect

Examples


# run CytoPipeline object first

outputDir <- base::tempdir()


rawDataDir <-
    system.file("extdata", package = "CytoPipeline")
experimentName <- "OMIP021_PeacoQC"
sampleFiles <- 
    file.path(
        rawDataDir, 
        list.files(rawDataDir, pattern = "Donor"))
jsonDir <- system.file("extdata", package = "CytoPipeline")
jsonPath <- file.path(jsonDir, "pipelineParams.json")

pipL2 <- CytoPipeline(
    jsonPath,
    experimentName = experimentName,
    sampleFiles = sampleFiles)

suppressWarnings(execute(
    pipL2,
    rmCache = TRUE,
    path = outputDir))
#> #####################################################
#> ### running SCALE TRANSFORMATION processing steps ###
#> #####################################################
#> Proceeding with step 1 [flowframe_read] ...
#> Proceeding with step 2 [remove_margins] ...
#> Removing margins from file : Donor1.fcs
#> Removing margins from file : Donor2.fcs
#> Proceeding with step 3 [compensate] ...
#> Proceeding with step 4 [flowframe_aggregate] ...
#> Proceeding with step 5 [scale_transform_estimate] ...
#> #####################################################
#> ### NOW PRE-PROCESSING FILE /__w/_temp/Library/CytoPipeline/extdata/Donor1.fcs...
#> #####################################################
#> Proceeding with step 1 [flowframe_read] ...
#> Proceeding with step 2 [remove_margins] ...
#> Removing margins from file : Donor1.fcs
#> Proceeding with step 3 [compensate] ...
#> Proceeding with step 4 [remove_doublets] ...
#> Proceeding with step 5 [remove_debris] ...
#> Proceeding with step 6 [remove_dead_cells] ...
#> Proceeding with step 7 [perform_QC] ...
#> Applying PeacoQC method...
#> Starting quality control analysis for Donor1.fcs
#> Calculating peaks
#> MAD analysis removed 30.75% of the measurements
#> The algorithm removed 30.75% of the measurements
#> Proceeding with step 8 [transform] ...
#> #####################################################
#> ### NOW PRE-PROCESSING FILE /__w/_temp/Library/CytoPipeline/extdata/Donor2.fcs...
#> #####################################################
#> Proceeding with step 1 [flowframe_read] ...
#> Proceeding with step 2 [remove_margins] ...
#> Removing margins from file : Donor2.fcs
#> Proceeding with step 3 [compensate] ...
#> Proceeding with step 4 [remove_doublets] ...
#> Proceeding with step 5 [remove_debris] ...
#> Proceeding with step 6 [remove_dead_cells] ...
#> Proceeding with step 7 [perform_QC] ...
#> Applying PeacoQC method...
#> Starting quality control analysis for Donor2.fcs
#> Calculating peaks
#> MAD analysis removed 24.38% of the measurements
#> The algorithm removed 24.38% of the measurements
#> Proceeding with step 8 [transform] ...

plotSelectedWorkflow(
    experimentName = experimentName,
    whichQueue = "pre-processing",
    sampleFile = sampleFiles[1],
    path = outputDir)

    
plotSelectedWorkflow(
    experimentName = experimentName,
    whichQueue = "scale transform",
    sampleFile = NULL,
    path = outputDir)