ReadInput {FlowSOM} | 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(), scale = FALSE, scaled.center = TRUE, scaled.scale = TRUE, silent = FALSE)
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 |
transform |
logical, does the data need to be transformed |
toTransform |
column names or indices that need to be transformed.
If |
transformFunction |
Defaults to logicleTransform() |
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
# Read from file fileName <- system.file("extdata","lymphocytes.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]]