SVGenes: a library for rendering genomic features in scalable vector graphic format

G J Etherington,D Maclean

doi:10.1093/bioinformatics/btt294

Abstract

Motivation: Drawing genomic features in attractive and informative ways is a key task in visualization of genomics data. Scalable Vector Graphics (SVG) format is a modern and flexible open standard that provides advanced features including modular graphic design, advanced web interactivity and animation within a suitable client. SVGs do not suffer from loss of image quality on re-scaling and provide the ability to edit individual elements of a graphic on the whole object level independent of the whole image. These features make SVG a potentially useful format for the preparation of publication quality figures including genomic objects such as genes or sequencing coverage and for web applications that require rich user-interaction with the graphical elements.Results: SVGenes is a Ruby-language library that uses SVG primitives to render typical genomic glyphs through a simple and flexible Ruby interface. The library implements a simple Page object that spaces and contains horizontal Track objects that in turn style, colour and positions features within them. Tracks are the level at which visual information is supplied providing the full styling capability of the SVG standard. Genomic entities like genes, transcripts and histograms are modelled in Glyph objects that are attached to a track and take advantage of SVG primitives to render the genomic features in a track as any of a selection of defined glyphs. The feature model within SVGenes is simple but flexible and not dependent on particular existing gene feature formats meaning graphics for any existing datasets can easily be created without need for conversion.Availability: The library is provided as a Ruby Gem from https://rubygems.org/gems/bio-svgenes under the MIT license, and open source code is available at https://github.com/danmaclean/bioruby-svgenes also under the MIT License.Contact: dan.maclean@tsl.ac.uk

Highlights

Visualization, analysis and communication of genome data is an important task in genomics
Genome browsers such as Gbrowse (Stein et al, 2002), JBrowse (Skinner et al, 2009), Savant (Fiume et al, 2010) and IGV (Thorvaldsdottir et al, 2013) provide interactive visualization of the data for whole genomes and draft assemblies. Output from these is typically limited to an exported bitmap or screen grab in the program’s particular fixed style. Graphics libraries such as GD and ImageMagick have been used in projects like BioPerl (Stajich et al, 2002) and BioRuby (Goto et al, 2010) to create uniquely styled bitmap images like PNG and JPEG programmatically
Interactive graphics can be provided in web-browsers through JavaScript libraries such as D3.js but there are no such libraries available for easy rendering of genomic data

Summary

INTRODUCTION

Visualization, analysis and communication of genome data is an important task in genomics. Numerous desktop computer programs exist for rendering images of genomic data, usually in analytic pipelines including Artemis (Carver et al, 2008) Genome browsers such as Gbrowse (Stein et al, 2002), JBrowse (Skinner et al, 2009), Savant (Fiume et al, 2010) and IGV (Thorvaldsdottir et al, 2013) provide interactive visualization of the data for whole genomes and draft assemblies. Output from these is typically limited to an exported bitmap or screen grab in the program’s particular fixed style. Interactive graphics can be provided in web-browsers through JavaScript libraries such as D3.js but there are no such libraries available for easy rendering of genomic data.

APPROACH

Workflow

CONCLUSION