NewData: NewData

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

NewData

Description

Map new data to a FlowSOM grid

Usage

NewData(
  fsom,
  input,
  madAllowed = 4,
  compensate = NULL,
  spillover = NULL,
  transform = NULL,
  toTransform = NULL,
  transformFunction = NULL,
  transformList = NULL,
  scale = NULL,
  scaled.center = NULL,
  scaled.scale = NULL,
  silent = FALSE
)

Arguments

fsom	FlowSOM object
input	A flowFrame, a flowSet or an array of paths to files or directories
madAllowed	A warning is generated if the distance of the new data points to their closest cluster center is too big. This is computed based on the typical distance of the points from the original dataset assigned to that cluster, the threshold being set to median + madAllowed * MAD. Default is 4.
compensate	logical, does the data need to be compensated. If NULL, the same value as in the original FlowSOM call will be used.
spillover	spillover matrix to compensate with. If NULL, the same value as in the original FlowSOM call will be used.
transform	logical, does the data need to be transformed. If NULL, the same value as in the original FlowSOM call will be used.
toTransform	column names or indices that need to be transformed. If NULL, the same value as in the original FlowSOM call will be used.
transformFunction	If NULL, the same value as in the original FlowSOM call will be used.
transformList	If NULL, the same value as in the original FlowSOM call will be used.
scale	Logical, does the data needs to be rescaled. If NULL, the same value as in the original FlowSOM call will be used.
scaled.center	See scale. If NULL, the same value as in the original FlowSOM call will be used.
scaled.scale	See scale. If NULL, the same value as in the original FlowSOM call will be used.
silent	Logical. If TRUE, print progress messages. Default = FALSE.

Details

New data is mapped to an existing FlowSOM object. The input is similar to the ReadInput function. A new FlowSOM object is created, with the same grid, but a new mapping, node sizes and mean values. The same preprocessing steps (compensation, transformation and scaling) will happen to this file as was specified in the original FlowSOM call. The scaling parameters from the original grid will be used.

Value

A new FlowSOM object

See Also

FlowSOMSubset if you want to get a subset of the current data instead of a new dataset

Examples

 # Build FlowSom result
 fileName <- system.file("extdata", "68983.fcs", package = "FlowSOM")
 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 <- FlowSOM(ff[1:1000, ], 
                          scale = TRUE, 
                          colsToUse = c(9, 12, 14:18),
                          nClus = 10)
   
   # Map new data
   fSOM2 <- NewData(flowSOM.res, ff[1001:2000, ])

saeyslab/FlowSOM documentation built on April 15, 2024, 1:03 p.m.