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Last data update: 2014.03.03

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

mnplot

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.

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)

Results


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> library(eisa)
Loading required package: isa2
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: AnnotationDbi
Loading required package: stats4
Loading required package: IRanges
Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/eisa/mnplot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: mnplot
> ### Title: Plot group means against each other, for an ISA module
> ### Aliases: mnplot ISAmnplot
> ### Keywords: cluster
> 
> ### ** 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)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>