plot.Corr {IdMappingAnalysis} | R Documentation

## Plot the density distributions for correlation object(s)

### Description

Plot the density distributions for a given Corr object or list of Corr objects. The method can be used as object specific as well as static. In the latter case the method can accept a list of Corr objects using Corr$plot(corrList) call signature.

### Usage

    ## S3 method for class 'Corr'
    plot(x, dataList=NULL, title="nonparametric density fit", lineColors=NULL, lineStyles=NULL, lineWidths=2, verbose=FALSE, cex.main=1.2, cex.lab=1, cex.axis=1, cex.legend=1, par.zoom=1, ...)

### Arguments

`dataList` | the list of Corr objects (used if static version of method invoked). Default is $NULL.
`title` | main plot title. Default is 'nonparametric density fit'.
`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`.
`cex.main` | Main title font size. Default is 1.2.
`cex.lab` | X and Y titles font size. Default is 1.
`cex.axis` | X and Y axis labels font size. Default is 1.
`cex.legend` | font size for the plot legend. Default is 1.
`par.zoom` | graphics parameters zoom factor. Scales the graphical parameters like cex, lwd, mai etc. Used to plot into the file based device with dimensions 'zoom' times bigger than for on-screen device.
`...` | additional graphical parameters

### Author(s)

Alex Lisovich, Roger Day

### See Also

For more information see `Corr`.

### Examples

     examples$corr$plot();

     #create a set of corr. objects for a given DB subset treating subset
     #as a full group and then plot the correlation densities including union
     corrSet<-examples$jointUniquePairs$getCorr(examples$corr,
    		groups=c("union","EnVision_Q","NetAffx_Q","DAVID_Q","EnVision_Q"),
    		full.group=TRUE,verbose=TRUE);
     Corr$plot(corrSet);

[Package IdMappingAnalysis version 1.28.0 Index]