Visualisation of data is an extremely common task in working with genomic data. Unfortunately, the libraries available for generating plots in Java are mostly geared towards applications and are not as easy to use or feature rich for use with scientific data.To ease plot generation, Groovy NGS includes the https://github.com/eseifert/gral Gral plotting library to support generation of plots by default, allowing any APIs from this library to be called to create visualisations. As with many Java based plotting APIs however, it is not well integrated with data types typically used in data analysis, requiring many API calls to generate a simple plot. Groovy NGS therefore includes a set of wrappers that make generation of useful plots directly from raw data very ergonomic. These APIs are based around the plotting libraries supported in the https://github.com/twosigma/beakerx BeakerX JupyterLab Extenions, allowing the same plots that are generated in notebooks to then be easily used offline in command line applications.Plots are created by creating a Plot object: groovy import gngs.plot.* p = new Plot() Most attributes of the plots are passed using Groovy's https://docs.groovy-lang.org/latest/html/documentation/#_named_parameters Map Constructor idiom, such that plot-level features are mostly configured in the constructor by passing them as attributes. An example of a plot with title, axis labels and X and Y ranges set for the plot area is as follows: groovy p = new Plot( title: 'An example plot', xLabel: 'This is the x axis', yLabel: 'This is the y axis', xBound: [0, 10], yBound: [0, 30] )

Once you have created a plot, you will likely want to save it to a file.This can easily be achieved by calling the save function: groovy p.save('example_plot.png') By default, images are saved resolution of 1024 x 800, but you can set this explicitly by passing width and height properties: groovy p.save('example_plot.png', width: 1600, height: 1200) At this stage, these will save an empty plot, because we have not added any data to it.

Data is added to plots by creating data objects and using Groovy's << operator on the plot object. The data objects themselves are created using the same map-constructor style syntax, and can be Line , Bars , Points , or Area objects: groovy p << new Line( x: [1,2,3,4,5], y: [1,4,9,16,25] ) Note that in most of these data objects, the actual position of the data points is expressed as x and y attributes of the objects.

Further attributes can be specified such as the color of the objects. The color can be specified as https://docs.oracle.com/javase%2F7%2Fdocs%2Fapi%2F%2F/java/awt/Color.html java.awt.Color objects, for which the built in predefined colors are often useful: groovy import java.awt.Color p << new Line( x: [1,2,3,4,5], y: [1,4,9,16,25], color: Color.red ) p << new Line( x: [1,2,3,4,5], y: [1,8,27,64,125], color: Color.blue )

To add a legend to the plot, specify the displayName attribute on each data object to be drawn: groovy import java.awt.Color p << new Line( x: [1,2,3,4,5], y: [1,4,9,16,25], color: Color.red, displayName: 'Square of Numbers' ) p << new Line( x: [1,2,3,4,5], y: [1,8,27,64,125], color: Color.blue, displayName: 'Cube of Numbers' )

As they are very common to show overall data properties, Groovy NGS supports two kinds of distribution plots that are especially easy to create: Density plots and Histograms. groovy p = new Plot(title: 'Guassian Distribution') p << new gngs.plot.bx.Density.Area( data: (1..100).collect { 5 + r.nextGaussian() } ) groovy h = new Histogram( title: "Gaussian Distribution", data: (1..500).collect { 5 + r.nextGaussian() } )

If you want to add more to the generated plots or manipulate the image in additional ways, you can generate the https://docs.oracle.com/javase/8/docs/api/java/awt/image/BufferedImage.html BufferedImage directly and use standard Java features to draw on it: groovy BufferedImage image = p.image Graphics2D imageGraphics = image.createGraphics() imageGraphics.drawRect(10,10, 20,20) ... As with saving the plot, you can specify the resolution: groovy BufferedImage image = p.getImage(1600, 1200) ...