condPlot {eisa} | R Documentation

## Plot sample scores of a transcription module

### Description

Creates a barplot of sample (=condition) scores, for a given transcription module. See details below.

### Usage

    condPlot (modules, number, eset, col = "white", all = TRUE, sep = NULL,
        sepcol = "grey", val = TRUE, srt = 90, adj.above = c(0, 0.5),
        adj.below = c(1, 0.5), plot.only = seq_len(ncol(eset)), ...)

### Arguments

`modules` | An `ISAModules` object.
`number` | An integer scalar, the module to plot.
`eset` | An `ExpressionSet` or `ISAExpressionSet` object. This is needed for calculating the scores of the samples that are not in the module, see the `all` argument. If an `ExpressionSet` object is supplied, then it is normalised by calling `ISANormalize` on it.
`col` | Color of the bars, it it passed to `barplot`, so it can be any format `barplot` accepts. E.g. it can be a character vector with different colors for the different bars.
`all` | Logical scalar, whether to plot all samples (if `TRUE`, the default), or just the ones that are included in the module.
`sep` | `NULL` or a numeric vector. If not `NULL`, then the bars are separated at the given positions with vertical lines. This is useful if you want to subdivide the samples into groups.
`sepcol` | The color of the separating lines (see the `sep` argument), if they are plotted.
`val` | Logical scalar, whether to add labels with the actual score values.
`srt` | Numeric scalar, the rotation angle of the text labels, this is passed to the `text` function.
`adj.above` | Adjustment of the text labels that are above the bars. This is passed to `text`, see its manual for details.
`adj.below` | Adjustments of the text labels that are below the bars. This is passed to `text`, see its manual for details.
`plot.only` | Numeric vector, if supplied it is used to plot a subset of samples only. By default all samples are plotted.
`...` | Additional argument, to be passed to `barplot`.

### Details

`condPlot` creates a barplot for the sample scores of an ISA transcription module. Each sample is represented as a bar.

These plots are useful if you want to show that a given transcription module separates the samples into two (or more) groups. You can assign different colors to the samples, based on some external information, e.g. case and control samples can be colored differently.

In most cases the scores are between minus one and one, but this is not necessarily true.

It is possible to assign scores to samples that are not part of the module, but this requires performing one (more precisely half) ISA iteration step. Currently the function always performs this extra step, even if the out-of-module samples are not plotted. Because the sample scores in a module are only approximately constant during ISA iteration, it might be possible that the plotted scores are slightly different than the ones stored in the `modules` variable.

### Value

None.

### 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

`ISA` and `ISAModules`.

### Examples

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

    col <- ifelse(grepl("^B", ALL$BT), "darkolivegreen", "orange")
    condPlot(ALLModulesSmall, 1, ALL, col=col)

[Package eisa version 1.38.0 Index]