plot.IdMapDiffCounts: Produce a fountain plot representing the quantitative...
In IdMappingAnalysis: ID Mapping Analysis

Description Usage Arguments Author(s) See Also Examples

Produce a fountain plot representing the quantitative relationship of the compound events <'excess both', 'excess left', 'excess right', 'same list', 'in left only', 'in right only', 'in neither' >

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## S3 method for class 'IdMapDiffCounts'
plot(x, valRange=c(-20, 20, 10), reverse=FALSE, pairLabels=NULL, guideline.col="darkgrey", guideline.lty=2, guideline.lwd=par.zoom, cols=c("red", "blue", "green"), sides=2, cex=1, cex.side=0.75 * cex, srt=0, adj=0.5, par.zoom=1, ...)

`valRange`	`numeric` vector of length 3 where the first and second elements are minimum and maximum count values to be displayed on horizontal axis and the third element is a distance between horizontal axis tick marks. Default is c(-20,20,10).
`reverse`	logical indicating the plot orientation (top to bottom or bottom to top)
`pairLabels`	optional decorated names for ID Map pair in consideration. If `NULL` (default), the original ID Map names are used.
`guideline.col`	guideline(horisontal group divider) lines color. Default is 'darkgrey'.
`guideline.lty`	guideline lines type. Default is 2 (dashed).
`guideline.lwd`	guideline lines color. Default is par.zoom.
`cols`	colors corresponding to the <A-AB, AB, B-A*B> events from which the plot is composed.
`sides`	How compound events labels and counts are placed on plot. Possible values are 1 or 2. If sides=1 both event labels and counts are placed on one (left) side. If sides=2 then labels are placed on left side and counts on the right.
`cex`	plot title font size.
`cex.side`	compound events side labels font size.
`srt`	compound events labels orientation.
`adj`	compound events labels position adjustment (0 - 1), where 0/1 corresponds to the minimum/maximum labels position shift inwards the plot.
`par.zoom`	graphics parameters zoom factor. Scales the graphical parameters like cex, lwd, mai etc.
`...`	Additional graphical parameters

Alex Lisovich, Roger Day

For more information see IdMapDiffCounts.

 #create IdMapDiffCounts object
 IDs<-IdMapBase$primaryIDs(examples$msmsExperimentSet);
 jointIdMap<-JointIdMap(examples$identDfList,primaryIDs=IDs);
 diffs<-jointIdMap$getDiff("NetAffx_F","DAVID_Q",verbose=TRUE);
 diffCounts<-IdMapDiffCounts(diffs);

 # fountain plot of DB pair differences
 # two-sided labels
 diffCounts$plot(sides=2);
 # one-sided labels
 diffCounts$plot(sides=1);