plotMDS: Create double-labeled MDS plot from (merged) ExpressionSet

Description Usage Arguments Examples

Description

Create Multidimensional Scaling (MDS) plot from ExpressionSet. Very similar to Principal Component Analysis (PCA) plots all samples are plotted in a two-dimensional space where both axis represent the two principle axis of expression variation. In this plot each sample can be labeled with a color and with a symbol.

Usage

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plotMDS(eset, colLabel, symLabel, legend=TRUE, file=NULL, ...)

Arguments

eset

ExpressionSet object.

colLabel

colname in pData(eset) to retrieve information for the labeling of samples with a color. All samples with the same value in pData(eset)[,colLabel] will share the same color.

symLabel

colname in pData(eset) to retrieve information for the labeling of samples with a symbol. All samples with the same value in pData(eset)[,symLabel] will share the same symbol.

legend

If TRUE a legend will be provided next to the MDS plot for both colLabel and symlabel.

file

If defined, the resulting plot will be stored as a pdf file instead of shown interactively.

...

Additional parameters for the 'plot' function (e.g. 'main').

Examples

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# retrieve two datasets:
library(inSilicoDb);
InSilicoLogin("[email protected]", "5c4d0b231e5cba4a0bc54783b385cc9a");
eset1 = getDataset("GSE18842", "GPL570", norm="FRMA", features="gene");
eset2 = getDataset("GSE31547", "GPL96",  norm="FRMA", features="gene");
esets = list(eset1,eset2);

# merge them using no additional merging technique and the 'COMBAT' method:
library(inSilicoMerging)
eset_FRMA = merge(esets);
eset_COMBAT = merge(esets, method="COMBAT");

# check available annotations:
colnames(pData(eset_FRMA))
table(pData(eset_FRMA)[,"Disease"]);
table(pData(eset_FRMA)[,"Study"]);

# Visual inspection of the two merged datasets through an MDS plot
plotMDS(eset_FRMA, colLabel="Disease", symLabel="Study")
plotMDS(eset_COMBAT, colLabel="Disease", symLabel="Study")

inSilicoMerging documentation built on Oct. 5, 2016, 4:16 a.m.