expPlot {eisa} | R Documentation

## 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`.

### 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.

### 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.

### Author(s)

Gabor Csardi csardi.gabor@gmail.com

### 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)
    }

[Package eisa version 1.39.0 Index]