corr.boxplot.JointUniquePairs: Boxplot of correlations by match group
In IdMappingAnalysis: ID Mapping Analysis

Description Usage Arguments Value Author(s) See Also Examples

Creates a boxplot of correlations data from the Corr object by a set of match groups from the UniquePairsMatch object, utilizing the JointUniquePairs$boxplot function

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## S3 method for class 'JointUniquePairs'
corr.boxplot(this, corr, idMapNames=NULL, show.None=FALSE, subsetting=FALSE, group.gap=0.2, cex.main=1.2, cex.lab=1, srt=0, adj=0, par.zoom=1, main=paste("Correlations (", colnames(corr)[3], ") by match group", sep = ""), plot=TRUE, verbose=FALSE, ...)

`corr`	Corr object which correlation values are used for boxplot.
`idMapNames`	Defines a subset of match group names to be plotted. If $NULL (default), all group names within the pairsMatch are used.
`subsetting`	If `TRUE`, interprets Corr subset as a full group or uses the original Corr as a full group otherwise. Default is `FALSE`.
`show.None`	If `TRUE`, includes a plot of subset of values not included into any other match group with 'None' label. Default is `FALSE`.
`group.gap`	The gap between match groups. Default is 0.2.
`cex.main`	Font size for plot main title. Default is 1.2.
`cex.lab`	Font size for X and Y axis titles. Default is 1.
`srt`	Match group label orientation (see par('srt')). Default is 0.
`adj`	`numeric` in a range (0..1) determening how close to the x-axis the group labels are, 1 being the closest and 0 is farthest. The default is 0.
`par.zoom`	Graphics parameters zoom factor. Scales the graphical parameters like cex, lwd, mai etc. Default is 1.
`main`	The main title. Default is 'Correlations (type) by match group', where type is derived from corr object ('spearman' or 'pearson').
`plot`	if `TRUE` (default) then a boxplot is produced. If not, the summaries which the boxplots are based on are returned.
`verbose`	If `TRUE` enables diagnostic messages. Default is `FALSE`.
`...`	Additional graphical parameters

Same as for boxplot in graphics package

Alex Lisovich, Roger Day

For more information see JointUniquePairs.

 #plot correlation probability distributions (boxplots) by match group
 mapNames=list(NetAffx_Q="Affy_Q",DAVID_F="D_F",EnVision_Q="EnQ");
 data = examples$jointUniquePairs$corr.boxplot(examples$corr,
	        idMapNames=mapNames,subsetting=TRUE,
              multiline=TRUE, srt=30, cex.lab=0.8, col.points="green" , main="");