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mdsPlot(dat, numPositions = 1000, sampNames = NULL, sampGroups = NULL, xlim, ylim, pch = 1, pal = brewer.pal(8, "Dark2"), legendPos = "bottomleft", legendNCol, main = NULL)
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
genomic positions with the most methylation variability when calculating distance between samples.par
for details.legend
for details.legend
for 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.
qcReport
, controlStripPlot
,
densityPlot
, densityBeanPlot
,
par
, legend
if (require(minfiData)) {
names <- pData(MsetEx)$Sample_Name
groups <- pData(MsetEx)$Sample_Group
mdsPlot(MsetEx, sampNames=names, sampGroups=groups)
}
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