perform QC with PeacoQC

this function is a wrapper around PeacoQC::PeacoQC() function. It also pre-selects the channels to be handled (=> all signal channels)

Usage

qualityControlPeacoQC(
  ff,
  preTransform = FALSE,
  transList = NULL,
  outputDiagnostic = FALSE,
  outputDir = NULL,
  ...
)

Arguments

ff

a flowCore::flowFrame

preTransform

if TRUE, apply the transList scale transform prior to running the gating algorithm

transList

applied in conjunction with preTransform

outputDiagnostic

if TRUE, stores diagnostic files generated by PeacoQC in outputDir directory

outputDir

used in conjunction with outputDiagnostic

...

additional parameters passed to PeacoQC::PeacoQC()

Value

a flowCore::flowFrame with removed low quality events from the input

Examples

rawDataDir <-
    system.file("extdata", package = "CytoPipeline")
sampleFiles <-
    file.path(rawDataDir, list.files(rawDataDir, pattern = "Donor"))

truncateMaxRange <- FALSE
minLimit <- NULL

# create flowCore::flowSet with all samples of a dataset
fsRaw <- readSampleFiles(
    sampleFiles = sampleFiles,
    whichSamples = "all",
    truncate_max_range = truncateMaxRange,
    min.limit = minLimit)

suppressWarnings(ff_m <- removeMarginsPeacoQC(x = fsRaw[[2]]))
#> Removing margins from file : Donor2.fcs
    
ff_c <-
    compensateFromMatrix(ff_m,
                         matrixSource = "fcs")        

transList <- 
    estimateScaleTransforms(        
        ff = ff_c,
        fluoMethod = "estimateLogicle",
        scatterMethod = "linear",
        scatterRefMarker = "BV785 - CD3")


ff_QualityControl <- suppressWarnings(
    qualityControlPeacoQC(
        ff_c,
        preTransform = TRUE,
        transList = transList,
        min_cells = 150,
        max_bins = 500,
        MAD = 6,
        IT_limit = 0.55,
        force_IT = 150, 
        peak_removal = (1/3),
        min_nr_bins_peakdetection = 10))
#> Applying PeacoQC method...
#> Starting quality control analysis for Donor2.fcs
#> Calculating peaks
#> MAD analysis removed 9.57% of the measurements
#> The algorithm removed 9.57% of the measurements