ReadInput: Read fcs-files or flowframes

In FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data

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(),
  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. If NULL and transform=TRUE, column names of $SPILL description in fcs file will be used.
transformFunction	Defaults to logicleTransform()
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

See Also

scale,BuildSOM

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,ff@description$SPILL)
ff <- flowCore::transform(ff,
                 flowCore::transformList(colnames(ff@description$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]]    
 

FlowSOM documentation built on Nov. 8, 2020, 6:40 p.m.