mnplot {eisa} | R Documentation

## Plot group means against each other, for an ISA module

### Description

Plot mean expression values for two sets of samples, against each other.

### Usage

    mnplot (x, expset, group, ...)
    ISAmnplot (modules, number, eset, norm = c("raw", "feature", "sample"),
         group, ...)

### Arguments

`x` | A character vector, the feature names for which the plot is created.
`expset` | An `ExpressionSet` object (`Biobase` package), or an expression matrix, with row names as feature names.
`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.
`group` | A factor that defines two groups to plot one against the other.
`modules` | An `ISAModules` object.
`number` | A numeric scalar, the number of the module for which the plot is created.
`...` | Additional arguments, they are passed to the `plot` function.

### Details

`mnplot` plots two group-means against each other, the mean expression of all the specified probes. The two groups are specified as a factor with two levels.

`ISAmnplot` calls `mnplot` and plots the mean expression of genes in an ISA module, again, for two groups.

### Value

Both functions return invisibly a matrix with two lines, the mean expression values for the two groups, for all the specified genes.

### 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 `GOmnplot` and `KEGGmnplot` functions in the `annotate` package.

### Examples

    data(ALLModulesSmall)
    library(ALL)
    data(ALL)
    group <- ifelse(grepl("^B", ALL$BT), "B-cell", "T-cell")
    ISAmnplot(ALLModulesSmall, 2, ALL, norm="feature", group=group)

[Package eisa version 1.36.0 Index]