flowPlot {flowViz}R Documentation

Standard Plots for Flow Cytometry Data

Description

A method that makes standard plots from a flowFrame. The user may also provide various filter or filterResult arguments to customize the plot.

Usage


flowPlot(x, ...)

## S4 method for signature 'flowFrame':
flowPlot(x, child, filter = NULL,
         plotParameters = c("FSC-H","SSC-H"),
         logx = FALSE, logy = FALSE,
         parent, colParent="Grey", colChild="Blue",
         showFilter = TRUE, gate.fill = "transparent",
         gate.border = "black", xlab, ylab, xlim, ylim,
         ...)

Arguments

x An object of class flowFrame that contains the data to be plotted.
child An optional argument of class filterResult that specifies a subset of the data that are included in the filterResult
filter
plotParameters
logx
logy
parent
colParent
colChild
showFilter
gate.fill
gate.border
xlab
ylab
xlim
ylim
...

Details

The plot that is most commonly used in flow cytometry data analysis is usuall called a "dot plot". In common statistical language, we would call this a scatter plot. The basic idea is a 2-dimensional plot that shows the location of every cell in regard to the measurements made on it, for example, forward scatter vs side scatter. Most applications will, in addition to the data, want to show information about one or more filters (gates). Since there can be a very large number of cells in a sample, it is common to show a smoothed version of the data that doesn't involve registering every point on the graph.

Author(s)

P. Haaland

See Also

flowCore

Examples


data(GvHD)
flowPlot(GvHD[["s5a01"]])
flowPlot(transform("SSC-H"=asinh,"FSC-H"=asinh) %on% GvHD[["s5a01"]])


[Package flowViz version 1.0.0 Index]