splom: Method implementing Lattice scatter plot matrices for flow...
In flowViz: Visualization for flow cytometry

Description Usage Arguments Details Author(s) See Also Examples

This function create Trellis scatter plots matrices (splom) from flow cytometry data.

1
2
3

## S4 method for signature 'flowFrame,missing'
splom(x, data, pscales, time,
  exclude.time = TRUE, names = FALSE, ...)

`x`	A formula describing the structure of the plot and the variables to be used in the display.
`data`	A `flowFrame` object that serves as the source of data.
`pscales`	This arguments is passed unchanged to the corresponding methods in lattice, and is listed here only because it provides a different default. See documentation for the original methods for details.
`time`	A character string giving the name of the data column recording time. If not provided, we try to guess from the available parameters.
`exclude.time`	Logical, specifying whether to exclude the time variable from a scatter plot matrix. Defaults to `TRUE`.
`names`	Logical specifying wether gate names should be added to the plot. Currently, this feature is not supported for splom plots.
`...`	More arguments, usually passed on to the underlying lattice methods.

The function draws a scatter plot matrix of the data for each flow parameter in a flowFrame. For the most, one can think about this as a rectangular arrangement of separate xyplots, and most of that functionality is also available here. To be more precise, the function repeatedly calls panel.xyplot.flowframe to do the actual plotting. Please see its documentation for details.

F. Hahne, D. Sarkar

Not all standard lattice arguments will have the intended effect, but many should. For a fuller description of possible arguments and their effects, consult documentation on lattice.

library(flowCore)
data(GvHD)
library(flowStats)

tf <- transformList(colnames(GvHD)[3:7], asinh)
dat <- tf %on% GvHD[[3]]


## scatter plot matrix of individual flowFrames
lattice.options(panel.error=NULL)
splom(dat)

splom(dat[,1:3], smooth = FALSE)


## displaying filters
rg <- rectangleGate("FSC-H"=c(200,400), "SSC-H"=c(300,700),
"FL1-H"=c(2,4), "FL2-A"=c(4,7))
splom(dat, filter=rg)

splom(dat, filter=rectangleGate("FSC-H"=c(400,800)))

splom(dat[,1:4], smooth = FALSE, filter=norm2Filter("FSC-H", "SSC-H", scale=1.5))