LogoJS: a Javascript package for creating sequence logos and embedding them in web applications
UMass Chan Affiliations
Program in Bioinformatics and Integrative BiologyDocument Type
Journal ArticlePublication Date
2020-03-17
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SUMMARY: Sequence logos were introduced nearly 30 years ago as a human-readable format for representing consensus sequences, and they remain widely used. As new experimental and computational techniques have developed, logos have been extended: extra symbols represent covalent modifications to nucleotides, logos with multiple letters at each position illustrate models with multi-nucleotide features, and symbols extending below the x-axis may represent a binding energy penalty for a residue or a negative weight output from a neural network. Web-based visualization tools for genomic data are increasingly taking advantage of modern web technology to offer dynamic, interactive figures to users, but support for sequence logos remains limited. Here we present LogoJS, a Javascript package for rendering customizable, interactive, vector-graphic sequence logos and embedding them in web applications. LogoJS supports all the aforementioned logo extensions and is bundled with a companion web application for creating and sharing logos. AVAILABILITY: LogoJS is implemented both in plain Javascript and ReactJS, a popular user-interface framework. The web application is hosted at logojs.wenglab.org. All major browsers and operating systems are supported. The package and application are open-source; code is available at GitHub. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.Source
Pratt H, Weng Z. LogoJS: a Javascript package for creating sequence logos and embedding them in web applications. Bioinformatics. 2020 Mar 17:btaa192. doi: 10.1093/bioinformatics/btaa192. Epub ahead of print. PMID: 32181813. Link to article on publisher's site
DOI
10.1093/bioinformatics/btaa192Permanent Link to this Item
http://hdl.handle.net/20.500.14038/29452PubMed ID
32181813Related Resources
ae974a485f413a2113503eed53cd6c53
10.1093/bioinformatics/btaa192