mnplot: Plot group means against each other, for an ISA module

In eisa: Expression data analysis via the Iterative Signature Algorithm

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 [e-mail]

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)

eisa documentation built on Nov. 8, 2020, 6:47 p.m.