Takes a Lucierna SingleColorQC .fcs, splits into percentiles, and plots the results.

Usage

Luciernaga_LinearSlices(
  x,
  subset,
  sample.name,
  removestrings,
  stats,
  returntype,
  probsratio = 0.1,
  output,
  desiredAF = NULL,
  legend = TRUE,
  droplowest = TRUE,
  titlename = NULL,
  returncutplot = FALSE,
  titleplot = NULL
)

Arguments

x: A GatingSet object
subset: The desired gating hierarchy level to look at the data
sample.name: Keyword for which sample name is stored
removestrings: A list of values to remove from the name
stats: Whether to use "mean" or "median"
returntype: Whether to return a "raw" or "normalized" value lineplot.
probsratio: Ratio increments to break quantiles into, default is set to 0.1.
output: Whether to return "plot" or "data"
desiredAF: Peak detector(ex. "V7-A") want to filter cells by before slicing, argument only used to override the main peak detector when a .fcs file has more than a single peak detector, default is set to NULL
legend: Returns the legend, default is TRUE.
droplowest: Removes lowest bin (percentile 0), default is TRUE
titlename: Default NULL, otherwise provide an alternate title.
returncutplot: Default FALSE, if true returns a histogram plot with locations where percentile slice occured.
titleplot: Default NULL, sets the returncutplot title

Value

Either ggplots or the summarized data.frame object preceding

Examples


library(flowCore)
library(flowWorkspace)
library(openCyto)
library(data.table)
library(dplyr)
library(purrr)
library(stringr)

File_Location <- system.file("extdata", package = "Luciernaga")
FCS_Files <- list.files(path = File_Location, pattern = ".fcs",
  full.names = TRUE)
CellSingleColorFiles <- FCS_Files[grep("Cells", FCS_Files)]
CellSingleColors <- CellSingleColorFiles[!str_detect("Unstained", CellSingleColorFiles)]

APC_Example <- CellSingleColors[grep("CD16_", CellSingleColors)]

MyCytoSet <- load_cytoset_from_fcs(APC_Example,
  truncate_max_range = FALSE,transformation = FALSE)
MyGatingSet <- GatingSet(MyCytoSet)
MyGates <- fread(file.path(path = File_Location, pattern = 'Gates.csv'))
MyGatingTemplate <- gatingTemplate(MyGates)
#> Adding population:singletsFSC
#> Adding population:singletsSSC
#> Adding population:singletsSSCB
#> Adding population:nonDebris
#> Adding population:lymphocytes
gt_gating(MyGatingTemplate, MyGatingSet)
#> Gating for 'singletsFSC'
#> done!
#> done.
#> Gating for 'singletsSSC'
#> done!
#> done.
#> Gating for 'singletsSSCB'
#> done!
#> done.
#> Gating for 'nonDebris'
#> done!
#> done.
#> Gating for 'lymphocytes'
#> The prior specification has no effect when usePrior=no
#> Using the serial version of flowClust
#> done!
#> done.
#> finished.
removestrings <- c(".fcs")

NormalizedSlices <- Luciernaga_LinearSlices(x=MyGatingSet[1],
 subset="lymphocytes",sample.name="GUID", removestrings=removestrings,
 stats="median", returntype="normalized", probsratio=0.1, output="plot",
 desiredAF="R1-A")