flowPlot: Standard Plots for Flow Cytometry Data

Description Usage Arguments Details Author(s) See Also Examples

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

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## 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

A filter, filterResult or filterResultList object.

plotParameters

A vector of charactors defining the x and y variables in terms of columns in the data.

logx, logy

Logical controlling wheterh the corresponding variables will be log transfromed before passing to the panel function. Default to FALSE.

parent

An optional argument of class filterResult that specifies a subset of the data that are inclueed in the filterResult.

colParent

Specifying the color for parent. See parent above.

colChild

Specifies the color for child. See chile above.

showFilter

Logical, specifying whether to show the filter.

gate.fill

Specifies the fill color of the gate. Default to transparent.

gate.border

Character or specifying the color of the gate border. Default to black.

xlab, ylab

Labels for data axes.

xlim, ylim

Numeric vectors of length 2 specifying axis limits.

...

More arguments, usually passed on to the underlying lattice methods.

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

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

flowViz documentation built on Nov. 8, 2020, 7:53 p.m.