ReadInput | R Documentation |
Take some input and return FlowSOM object containing a matrix with the preprocessed data (compensated, transformed, scaled)
ReadInput(
input,
pattern = ".fcs",
compensate = FALSE,
spillover = NULL,
transform = FALSE,
toTransform = NULL,
transformFunction = flowCore::logicleTransform(),
transformList = NULL,
scale = FALSE,
scaled.center = TRUE,
scaled.scale = TRUE,
silent = FALSE
)
input |
a flowFrame, a flowSet, a matrix with column names or an array of paths to files or directories |
pattern |
if input is an array of file- or directorynames, select only files containing pattern |
compensate |
logical, does the data need to be compensated |
spillover |
spillover matrix to compensate with
If |
transform |
logical, does the data need to be transformed |
toTransform |
column names or indices that need to be transformed.
Will be ignored if |
transformFunction |
Defaults to logicleTransform() |
transformList |
transformList to apply on the samples. |
scale |
logical, does the data needs to be rescaled |
scaled.center |
see |
scaled.scale |
see |
silent |
if |
FlowSOM object containing the data, which can be used as input for the BuildSOM function
scale
, BuildSOM
# Read from file
fileName <- system.file("extdata", "68983.fcs", package = "FlowSOM")
flowSOM.res <- ReadInput(fileName, compensate = TRUE, transform = TRUE,
scale = TRUE)
# Or read from flowFrame object
ff <- flowCore::read.FCS(fileName)
ff <- flowCore::compensate(ff, flowCore::keyword(ff)[["SPILL"]])
ff <- flowCore::transform(ff,
flowCore::transformList(colnames(flowCore::keyword(ff)[["SPILL"]]),
flowCore::logicleTransform()))
flowSOM.res <- ReadInput(ff, scale = TRUE)
# Build the self-organizing map and the minimal spanning tree
flowSOM.res <- BuildSOM(flowSOM.res, colsToUse = c(9, 12, 14:18))
flowSOM.res <- BuildMST(flowSOM.res)
# Apply metaclustering
metacl <- MetaClustering(flowSOM.res$map$codes,
"metaClustering_consensus", max = 10)
# Get metaclustering per cell
flowSOM.clustering <- metacl[flowSOM.res$map$mapping[, 1]]
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