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MmPalateMiRNA (version 1.22.0)

MADvsMedianPlot: Spread vs location of probe intensities

Description

Plots of the spread (median absolute deviation) versus the location (median) of probe intensity levels.

Usage

MADvsMedianPlot(x, ...)


"MADvsMedianPlot"( x, channel=c("G", "R"), group=NULL, subset=NULL,  ...)

Arguments

x
A list containing MAList and/or NChannelSet objects
channel
The channel to use for calculating distances, one of either "G" (green or control channel) or "R" (red or experimental channel)
group
An optional character string specifying the name of a factor to create separate panel displays, which must be in x$genes (for RGList objects)
subset
An optional character vector specifying the which levels of group to use in creating separate panel displays
...
arguments to pass to densityplot

Methods

signature(x = "list")
The method for list objects is intended to work with lists of normalized data sets, as either MAList or NChannelSet objects. This method will produce separate panel displays for each normalized data set, additionally color-coded by the group argument if supplied.

References

D. Sarkar, R. Parkin, S. Wyman, A. Bendoraite, C. Sather, J. Delrow, A. K. Godwin, C. Drescher, W. Huber, R. Gentleman, and M. Tewari. Quality assessment and data analysis for microRNA expression arrays. Nucleic Acids Res, 37(2):e17, 2009.

See Also

levelplot for pairwise distance plots between arrays, densityplot for density plots of log2 intensity values, and MAplot for MA plots.

Examples

Run this code
data(PalateData)
reducedSet <- filterArray(PalateData, keep=c("MIR", "LET", "POSCON", "CALIB"),
                          frac=1.1, number=3, reps=4)
ndata.none <- normalizeWithinArrays(reducedSet, method="none")
ndata.median <- normalizeWithinArrays(reducedSet, method="median")
ndata.loess <- normalizeWithinArrays(reducedSet, method="loess")
ndata.quantile <- normalizeBetweenArrays(reducedSet, method="quantile")
ndata.all <- list(ndata.none, ndata.median, ndata.loess, 
                  ndata.quantile)
res <- MADvsMedianPlot(ndata.all, channel="R", group="probe.type",                  
                 subset=c("MMU miRNAs", "Other miRNAs", "Control"))
print(res)

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