eisa (version 1.24.0)

expPlot: Expression matrix plots for ISA modules

Description

These functions create an expression matrix plot for an ISA module. The gene and sample scores are also plotted.

Usage

expPlotCreate (eset, modules, which, norm = c("sample", "raw", "feature"))
expPlot (epo, scores = TRUE)                                              
expPlotColbar (epo)

Arguments

eset

An ExpressionSet or ISAExpressionSet object. If an ExpressionSet object is supplied (and the norm argument is not set to ‘raw’), then it is normalised by calling ISANormalize on it. A subset of eset is selected that corresponds to the features included in modules.

norm

Character constant, specifies whether and how to normalize the expression values to plot. ‘raw’ plots the raw expression values, ‘feature’ the expression values scaled and centered for each feature (=gene) separately and if ‘sample’ is specified then the expression values are centered and scaled separately for each sample.

modules

An ISAModules object.

which

Numeric scalar, which module to plot.

scores

Logical scalar, whether to plot the scores as well.

epo

An object returned by expPlotCreate.

Value

expPlotCreate returns an ISAexpPlot object. It is a named list and has several entries, the important ones:

width

Numeric scalar, the optimal width of the plot.

height

Numeric scalar, the optimal height of the plot.

expPlot returns, invisibly, a named list with members:

coords

A list with two entries: x and y, both numeric vectors of length two. They give the position of the actual expression matrix on the plot.

gene.width

Numeric scalar, the width of one box on the image plot, in pixels; if the image size is exactly the suggested one.

cond.height

Numeric scalar, the height of one box on the image plot, in pixels; if the image size is exactly the suggested one.

expPlotColbar returns NULL, invisibly.

Details

expPlotCreate creates an object that contains all data for performing the image plot and returns it. The reason for not plotting it directly is, that the size of the plot is usually different in different cases, and the opening of the graphics device is delayed until expPlotCreate returns.

In the returned object, the weight and height entries give the optimal size of the image, in pixels.

expPlot creates the expression plot.

expPlotColbar plots a color bar for the expression plot.

References

Bergmann S, Ihmels J, Barkai N: Iterative signature algorithm for the analysis of large-scale gene expression data Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Mar;67(3 Pt 1):031902. Epub 2003 Mar 11.

See Also

The vignette in the eisa package for other ISA visualizations. The ExpressionView package for an interactive version.

Examples

data(ALLModulesSmall)
library(ALL)
data(ALL)

ep <- expPlotCreate(ALL, ALLModulesSmall, 1)
ep

if (interactive()) {
  expPlot(ep)
}