plotBins: Plot bins

In HELP: Tools for HELP data analysis

Description

Plot densities of multiple bins of data, divided by a sliding window approach

Usage

plotBins(x, y, ...)

Arguments

x	the vector of numerical data to be plotted. If x is a matrix it is interpreted as a vector. x can also be of class "ExpressionSet".
y	an additional vector of numerical data to be used for binning. If y is a matrix it is interpreted as a vector. y can also be of class "ExpressionSet".
...	Arguments to be passed to methods (see plotBins-methods): element which element of AssayData to use for a given ExpressionSet input (default is "exprs") sample which element of sampleNames to use as data (default is 1). Can be a character matching a sample name or simply an integer indicating which sample to choose. See getSamples. feature which element of featureData to use as binning variable (default is 1). Can be a character matching varLabel or simply an integer indicating which feature to choose. See getFeatures. num.bins number of bins (default is 10) used to divide the data num.steps number of steps (default is 3) used to create bin offsets, resulting in bins of sliding windows mode the binning mode to be used. This must be either "continuous" or "discrete". "continuous" mode will divide the data into density-dependent bins. "discrete" mode will divide the data uniformly by binning data values. show.avg logical; if TRUE, plots overall density in addition to densities per bin. If FALSE (default), overall density plot is omitted. main an overall title for the plot: see title. xlab a title for the x axis: see title. ylab a title for the y axis: see title. na.rm logical; if TRUE (default), missing values are removed from x and y. If FALSE any missing values cause an error. \dots other arguments to be passed to plot. See plot.

Author(s)

Reid F. Thompson ([e-mail])

See Also

plotBins-methods, density, quantile

Examples

#demo(pipeline,package="HELP")

x <- 1:1000
y <- sample(1:50,size=1000,replace=TRUE)
plotBins(x,y,show.avg=TRUE,main="Random binning data",xlab="1:1000")

#rm(x,y)

HELP documentation built on Nov. 8, 2020, 11:08 p.m.