Journal Article

Visualization of protein sequence features using JavaScript and SVG with pViz.js

Kiran Mukhyala and Alexandre Masselot

in Bioinformatics

Volume 30, issue 23, pages 3408-3409
Published in print December 2014 | ISSN: 1367-4803
Published online August 2014 | e-ISSN: 1460-2059 | DOI: https://dx.doi.org/10.1093/bioinformatics/btu567
Visualization of protein sequence features using JavaScript and SVG with pViz.js

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Summary: pViz.js is a visualization library for displaying protein sequence features in a Web browser. By simply providing a sequence and the locations of its features, this lightweight, yet versatile, JavaScript library renders an interactive view of the protein features. Interactive exploration of protein sequence features over the Web is a common need in Bioinformatics. Although many Web sites have developed viewers to display these features, their implementations are usually focused on data from a specific source or use case. Some of these viewers can be adapted to fit other use cases but are not designed to be reusable. pViz makes it easy to display features as boxes aligned to a protein sequence with zooming functionality but also includes predefined renderings for secondary structure and post-translational modifications. The library is designed to further customize this view. We demonstrate such applications of pViz using two examples: a proteomic data visualization tool with an embedded viewer for displaying features on protein structure, and a tool to visualize the results of the variant_effect_predictor tool from Ensembl.

Availability and implementation: pViz.js is a JavaScript library, available on github at https://github.com/Genentech/pviz. This site includes examples and functional applications, installation instructions and usage documentation. A Readme file, which explains how to use pViz with examples, is available as Supplementary Material A.

Contact: masselot.alexandre@gene.com

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  1183 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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