mdsPlot: Multi-dimensional scaling plots giving an overview of...

In kasperdanielhansen/minfi: Analyze Illumina Infinium DNA methylation arrays

Multi-dimensional scaling plots giving an overview of similarities and differences between samples.

Description

Multi-dimensional scaling (MDS) plots showing a 2-d projection of distances between samples.

Usage

mdsPlot(dat, numPositions = 1000, sampNames = NULL, sampGroups = NULL, xlim, ylim,
    pch = 1, pal = brewer.pal(8, "Dark2"), legendPos = "bottomleft",
    legendNCol, main = NULL)

Arguments

dat	An RGChannelSet, a MethylSet or a matrix. We either use the getBeta function to get Beta values (for the first two) or we assume the matrix contains Beta values.
numPositions	Use the numPositions genomic positions with the most methylation variability when calculating distance between samples.
sampNames	Optional sample names. See details.
sampGroups	Optional sample group labels. See details.
xlim	x-axis limits.
ylim	y-axis limits.
pch	Point type. See par for details.
pal	Color palette.
legendPos	The legend position. See legend for details.
legendNCol	The number of columns in the legend. See legend for details.
main	Plot title.

Details

Euclidean distance is calculated between samples using the numPositions most variable CpG positions. These distances are then projected into a 2-d plane using classical multidimensional scaling transformation.

Value

No return value. Plots are produced as a side-effect.

Author(s)

Martin Aryee [e-mail].

References

I Borg, P Groenen. Modern Multidimensional Scaling: theory and applications (2nd ed.) New York: Springer-Verlag (2005) pp. 207-212. ISBN 0387948457.

http://en.wikipedia.org/wiki/Multidimensional_scaling

See Also

qcReport, controlStripPlot, densityPlot, densityBeanPlot, par, legend

Examples

if (require(minfiData)) {

names <- pData(MsetEx)$Sample_Name
groups <- pData(MsetEx)$Sample_Group
mdsPlot(MsetEx, sampNames=names, sampGroups=groups)

}

kasperdanielhansen/minfi documentation built on May 4, 2024, 12:04 p.m.