corr.plot.JointUniquePairs: Plot the density distributions for a set of correlation...
In IdMappingAnalysis: ID Mapping Analysis

Description Usage Arguments Value Author(s) See Also Examples

Plot the density distributions for a set of correlation objects derived from JointUniquePairs and Corr objects with optional subsetting by a group of ID Maps. This is achived by first creating a correlation object from the JointUniquePairs and Corr objects with optional subsetting by a group of ID Maps and then calling the Corr.plot() on a resulting set of correlation objects.

1 2	## S3 method for class 'JointUniquePairs' corr.plot(this, corr, idMapNames=NULL, plot.Union=TRUE, subsetting=FALSE, lineColors=NULL, lineStyles=NULL, lineWidths=2, verbose=FALSE, ...)

`corr`	Corr object.
`idMapNames`	If not `NULL`, defines the subset of ID Maps from JointUniquePairs on which the full event group is to be formed. Default is `NULL`.
`plot.Union`	If `TRUE` (default), plots also the density of the correlation object corrsesponding to the union of a set of correlation objects.
`subsetting`	If `TRUE`, subsets the Corr on a group of ID Maps or uses the original Corr otherwise. Default is `FALSE`.
`lineColors`	The `vector` of line colors (recycled if necessary) for plotting the distributions of different Corr objects. If `NULL` (default), the predefined set of colors is used.
`lineStyles`	The `vector` of line styles (recycled if necessary) for plotting the distributions of different Corr objects. If `NULL` (default), the predefined set of line styles is used.
`lineWidths`	The `vector` of line widths (recycled if necessary) for plotting the distributions of different Corr objects. Default is 2.
`verbose`	If `TRUE` enables diagnostic messages. Default is `FALSE`.
`...`	Additional graphical parameters

The list of Corr objects which data densities are plotted

Alex Lisovich, Roger Day

For more information see JointUniquePairs.

 #plot the correlation densities of a Corr object (corr.spearman) on a given DB subset
 corrSet<-examples$jointUniquePairs$corr.plot(examples$corr,
             idMapNames=c("NetAffx_Q","DAVID_Q","EnVision_Q"),
	       plot.Union=TRUE,subsetting=TRUE,verbose=TRUE);
 names(corrSet);