R: Read fcs-files or flowframes

ReadInput {FlowSOM}

R Documentation

Read fcs-files or flowframes

Description

Take some input and return FlowSOM object containing a matrix with the preprocessed data (compensated, transformed, scaled)

Usage

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
)

Arguments

`input`	a flowFrame, a flowSet 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 `NULL` and compensate = `TRUE`, we will look for `$SPILL` description in fcs file.
`transform`	logical, does the data need to be transformed
`toTransform`	column names or indices that need to be transformed. Will be ignored if `transformList` is given. If `NULL` and transform = `TRUE`, column names of `$SPILL` description in fcs file will be used.
`transformFunction`	Defaults to logicleTransform()
`transformList`	transformList to apply on the samples.
`scale`	logical, does the data needs to be rescaled
`scaled.center`	see `scale`
`scaled.scale`	see `scale`
`silent`	if `TRUE`, no progress updates will be printed

Value

FlowSOM object containing the data, which can be used as input for the BuildSOM function

Examples

# 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]]