remove dead cells from a flowFrame, using manual gating in the FSC-A, '(a)Live/Dead' 2D representation. The function uses flowCore::polygonGate()

removeDeadCellsManualGate(
  ff,
  preTransform = FALSE,
  transList = NULL,
  FSCChannel,
  LDMarker,
  gateData,
  ...
)

Arguments

ff

a flowCore::flowFrame

preTransform

boolean, if TRUE: the transList list of scale transforms will be applied first on the LD channel.

transList

applied in conjunction with preTransform == TRUE

FSCChannel

a character containing the exact name of the forward scatter channel

LDMarker

a character containing the exact name of the marker corresponding to (a)Live/Dead channel, or the Live/Dead channel name itself

gateData

a numerical vector containing the polygon gate coordinates first the FSCChannel channel coordinates of each points of the polygon gate, then the LD channel coordinates of each points (prior to scale transform)

...

additional parameters passed to flowCore::polygonGate()

Value

a flowCore::flowFrame with removed dead cells 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")    
#> Compensating file : Donor2.fcs
                         
remDeadCellsGateData <- c(0, 0, 250000, 250000,
                          0, 650, 650, 0)  

ff_lcells <-
    removeDeadCellsManualGate(ff_c,
                              FSCChannel = "FSC-A",
                              LDMarker = "L/D Aqua - Viability",
                              gateData = remDeadCellsGateData)