Keywords
BioJS, data visualisation, genome browsers
This article is included in the Bioinformatics gateway.
This article is included in the BioJS collection.
This article is included in the EMBL-EBI collection.
BioJS, data visualisation, genome browsers
In the new version we have updated the availability sources, and some reference details based on the referees' comments.
See the authors' detailed response to the review by Stefan Thomas Lang
See the authors' detailed response to the review by Robert Buels
See the authors' detailed response to the review by Phil Lord
Numerous web applications exist for visualisation of biological data. Data can be prepared for visualisation using a variety of formats, one of which is the widely used wiggle (wig) file. A wiggle file contains text that defines either a feature or a data track. The wiggle format was developed by the UCSC genome browser1 and then quickly adopted by other initiatives2,3. Web applications such as genome browsers rely heavily on JavaScript, a popular language for processing and rendering client-side information in a web browser. Despite their widespread use in bioinformatics, biological web applications are usually implemented with no standard reutilisation guidelines in mind, hence BioJS was developed4. BioJS code contains proper guidelines on how to use the components and how the API can be implemented to interact with other components.
BioJS is an open source JavaScript library of components for the visualisation of biological data on the web. Here we present wigExplorer, a standard, portable BioJS component designed to easily render wig data format files. wigExplorer can be integrated and controlled from other applications. To our knowledge, this is the first modular component to visualise wig data that complies with BioJS standards.
wigExplorer is fully integrated in the BioJS project. It follows the standards set by the BioJS registry5, a centralised repository of BioJS components hosted at the European Bioinformatics Institute (EBI). Having wigExplorer in the BioJS registry is advantageous because it promotes i) easy discoverability for the component, ii) collaborative development with other members of the BioJS community and iii) reutilisation by third party applications. In the BioJS registry, component APIs are exposed, i.e., events and methods are defined and documented so that other BioJS components can interact with each other. By following these conventions, wigExplorer is able to interact with other components on the same web page, enriching the overall experience for the user. The code below shows how to incorporate wigExplorer into a web application. Only three configuration elements are needed: the target HTML element in which the component will be rendered, the background colour of the component, and the file path containing the wig data. Wig files contain minimalistic information of genomic data wigExplorer and can handle a large genomic region such as a chromosome (tested with a single file containing 12 chromosome with average length of 60 Mb), but this depends on the richness of the data rather than the length of the genomic region.
var instance = new Biojs.wigExplorer({ target: "YourOwnDivId", selectionBackgroundColor: ’<background-colour>’, dataSet: "<path–to–file>" });
wigExplorer uses D3.js, the data-driven documents JavaScript library6, to generate graphical representations from wig data. D3.js handles the manipulation of the data documents, the reading of wig data as text format and their conversion to an area chart format. On the top right side, wigExplorer contains a dropdown to toogle between different references from the wig file. To control the visual aspect of the wig data, wigExplorer contains simple controls for zooming and panning. It is also possible to zoom and pan using provided API.
instance._updateDraw(start, end)
wigExplorer can be used to visualise genomic data in different ways. An application is shown in Figure 1, depicting single nucleotide polymorphism (SNP) density data from a genomic annotation in the tomato genome. Here chromosome 2 is zoomed in to show the genomic interval contained between position 2.5M and 47.5M. The SNP density data contained in the wig data file are presented as bins, where the Y axis indicates the number of SNPs contained in each bin. The screenshot shows a dramatic change in the density of SNPs just after the 24M bin mark of the chromosome, suggesting a potential boundary for an introgression segment introduced from a closely related tomato species. Other potential applications of wigExplorer may involve the visualisation of gene expression and alignment data.
The top controls are designed to toogle between different references as well as zoom and pan. Peaks show SNP density of 1kb size bins. A change of SNP density can be observed around the 24M mark, with a slightly greater density of SNPs on the right, indicative of a potential introgression segment from another related species.
Third party browsers are also using wigExplorer. A screenshot of the TGAC Browser7 is shown in Figure 2 using wigExplorer to depict Myzus spp. scaffold 1 zoomed in between regions 714K and 727K. Here strandspecific RNA-Seq paired-end read coverage is shown as a wig track. The track below shows a closely related annotated species gene set for comparison. This comparison suggests a potential gene extension in both forward and reverse orientation.
The wigExplorer component provides a platform to visualise biological data in wig format. wigExplorer can be easily integrated with other web components or extended to provide new functionality. We expect this component to be particularly useful for visualisation in a variety of data types such as SNP density, alignments and gene expression. Like any other BioJS component, wigExplorer requires little technical knowledge for its utilisation.
Zenodo: wigExplorer, a BioJS component to visualise wig data_v2, doi: 10.5281/zenodo.85168
GitHub: BioJS, http://github.com/biojs/biojs/releases/tag/v1.0;
AT and RJ developed the code for wigExplorer. MC and GK created the user cases for Figure 1 and Figure 2 respectively. AT, RD, MC and GK wrote the paper.
AT, GK and RD were supported by the UK Biotechnology and Biological Sciences Research Council (BBSRC) National Capability Grant (BB/J010375/1) at Earlham Institute.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
We are grateful to all BioJS developers who have contributed their work under an open source license. We are thankful to David Swarbreck at Earlham Institute for his advice on the data shown in Figure 2.
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Competing Interests: No competing interests were disclosed.
Competing Interests: No competing interests were disclosed.
Competing Interests: No competing interests were disclosed.
Competing Interests: No competing interests were disclosed.
Competing Interests: No competing interests were disclosed.
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