getQuantiles | R Documentation |
getQuantiles
getQuantiles(
files,
channels,
nQ = 99,
minCells = 50,
quantileValues = NULL,
transformList = NULL,
labels = NULL,
selection = NULL,
verbose = FALSE,
plot = FALSE,
...
)
files |
Full paths of to the fcs files of the samples |
channels |
Names of the channels to compute the quantiles for |
nQ |
Number of quantiles to compute Default = 99, which results in quantiles for every percent of the data. Ignored if quantileValues is given. |
minCells |
Minimum number of cells required to compute trust-worthy quantiles. Otherwise NA is returned. Default = 50. |
quantileValues |
Vector of length with values between 0 and 1, giving the percentages at which the quantiles should be computed. If NULL (default), the quantiles will be evenly distributed, including 0 and 1. |
transformList |
Transformation list to pass to the flowCore
|
labels |
A label for every file, indicating to which group it belongs. If multiple files have the same label, they get aggregated. If NULL, all files are handled separately. |
selection |
List with indexation vector for every file. |
verbose |
If TRUE, extra output is printed. Default = FALSE |
plot |
If TRUE, plots are generated showing all quantiles. Default = FALSE. |
... |
Additional arguments to pass to read.FCS |
dir <- system.file("extdata", package = "CytoNorm")
files <- list.files(dir, pattern = "fcs$")
ff <- flowCore::read.FCS(file.path(dir, files[1]))
channels <- grep("Di$", flowCore::colnames(ff), value = TRUE)
transformList <- flowCore::transformList(channels,
cytofTransform)
quantiles <- getQuantiles(files = file.path(dir, files),
channels = channels,
transformList = transformList)
pheatmap::pheatmap(quantiles[[1]],
cluster_rows = FALSE,
cluster_cols = FALSE,
labels_col =
paste0(FlowSOM::GetMarkers(ff, colnames(quantiles[[1]])),
" (", colnames(quantiles[[1]]), ")"),
main = files[1])
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