expression_profiles: Plots the individual expression profile of a gene in samples...
In kevinrue/GOexpress-release: Visualise microarray and RNAseq data using gene ontology annotations

Description Usage Arguments Details Value Author(s) References See Also Examples

This function will plot the expression profile of a gene in individual samples series across a valid X-axis variable in the phenodata, while colouring sample groups according to another variable in the phenodata, and using different line types according to yet another (or the same) variable in the phenodata.

expression_profiles(
    gene_id, result, eSet, x_var, seriesF, subset=NULL,
    colourF=result$factor, linetypeF=colourF, line.size=1.5,
    xlab=x_var, ylab="log2(cpm)", ylim=range(exprs(eSet)),
    col.palette="Accent",
    col=brewer.pal(n=length(levels(pData(eSet)[,colourF])),
                    name=col.palette),
    lty=1:length(levels(pData(eSet)[,linetypeF])),
    title=NULL, title.size=2, axis.title.size=20,
    axis.text.size=15, axis.text.angle=0,
    legend.title.size=20, legend.text.size=15,
    legend.key.size=30)

`gene_id`	An gene or probeset identifier present in `rownames(expr_data)`.
`result`	An output of the `GO_analyse()` or `subset_scores()` function.
`eSet`	`ExpressionSet` of the `Biobase` package including a gene-by-sample expression matrix in the `AssayData` slot, and a phenotypic information data-frame in the `phenodate` slot. In the expression matrix, row names are Ensembl gene identifiers or probeset identifiers, and column names are sample identifiers. In the phentypic data-frame, row names are sample idenfifiers, column names are grouping factors and phenotypic traits usable for the one-way ANOVA.
`x_var`	A column name in `phenodata` to plot on the X-axis. If representing time on the X-axis, users should store the time-points as numeric values in the `AnnotatedDataFrame` to adequately space the time-points.
`seriesF`	A column name in `phenodata` to track samples of an identical series across the X-axis. The combination of `seriesF` and `x_var` should uniquely identify each sample in `eSet`.
`subset`	A named list to subset `eSet`. Names must be column names existing in colnames(pData(eSet)). Values must be vectors of values existing in the corresponding column of pData(eSet).
`colourF`	A column name in `phenodata` to colour the corresponding groups of samples. The factor specified in the initial `GO_analyse()` call is used by default.
`linetypeF`	A column name in `phenodata` to assign a different line type to the corresponding groups of samples. Default mirrors `colourF`.
`line.size`	The width of the plotted lines. Default is 1.5.
`xlab`	Title of the X-axis. Default is tha value of `x_var`.
`ylab`	Title of the Y-axis. Default is "log2(cpm)".
`ylim`	Numeric vector of length 2 specifying the lower and upper bounds of the Y axis. Default is scaled to the full range of expression values in the expression dataset, to ease comparison of different genes. If set to NULL, the axis will be scaled to fit the plotted data only.
`col.palette`	A valid `RColorBrewer` palette name to fetch the colormap from. Default is palette "Accent".
`col`	A vector of color names or codes. The number of colors provided must match the number of levels of the factor `colourF`. If specified, overrides argument `col.palette`. Default colours are obtained from the `col.palette`.
`lty`	A vector of numeric values corresponding to line types. The number of line types provided must match the number of levels of the factor `linetypeF`. Default line types are `1:length(levels(pData(eSet)[, linetypeF]))`.
`title`	Changes the plot title. Default is a combination of the gene id and the associated gene.
`title.size`	Changes the font size of the title. Default is 2.
`axis.title.size`	Changes the font size of the axes title. Defalt is 20.
`axis.text.size`	Changes the font size of the axes text labels. Default is 15.
`axis.text.angle`	Changes the angle of the X axis text labels. Default is 0 (horizontal).
`legend.title.size`	Changes the font size of the legend title. Default is 20.
`legend.text.size`	Changes the font size of the legend text labels. Default is 15.
`legend.key.size`	Changes the size of the legend keys (in points). Default is 30.

In order to track and visualise individual sample series, each sample in the ExpressionSet should be associated with a unique combination of seriesF and x_var. This may require the generation of a new factor in the phenodata, combining all experimental factors except that plotted on the X-axis. See below for an example on the training dataset.

The ggplot object.

Kevin Rue-Albrecht

ggplot2 package.

Packages Biobase and ggplot2 , methods expression_plot_symbol and expression_plot_symbol.

# load the sample output data
data(AlvMac_results)

AlvMac$Series <- paste(AlvMac$Animal, AlvMac$Treatment, sep="_")

expression_profiles(
    gene_id = "ENSBTAG00000047107", result = AlvMac_results,
    eSet=AlvMac, x_var = "Timepoint", seriesF="Series",
    legend.title.size=10, legend.text.size=10, legend.key.size=15)

expression_profiles(
    gene_id = "ENSBTAG00000047107", result = AlvMac_results,
    eSet=AlvMac, x_var = "Timepoint", seriesF="Series",
    linetypeF="Animal", 
    legend.title.size=10, legend.text.size=10, legend.key.size=15)