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. 2021 Sep 29;37(18):3017-3018.
doi: 10.1093/bioinformatics/btab186.

LocusZoom.js: interactive and embeddable visualization of genetic association study results

Andrew P Boughton  1 , Ryan P Welch  1 , Matthew Flickinger  1 , Peter VandeHaar  1 , Daniel Taliun  1 , Gonçalo R Abecasis  1 , Michael Boehnke  1
Affiliations

LocusZoom.js: interactive and embeddable visualization of genetic association study results

Andrew P Boughton et al. Bioinformatics. .

Abstract

Summary: LocusZoom.js is a JavaScript library for creating interactive web-based visualizations of genetic association study results. It can display one or more traits in the context of relevant biological data (such as gene models and other genomic annotation), and allows interactive refinement of analysis models (by selecting linkage disequilibrium reference panels, identifying sets of likely causal variants, or comparisons to the GWAS catalog). It can be embedded in web pages to enable data sharing and exploration. Views can be customized and extended to display other data types such as phenome-wide association study (PheWAS) results, chromatin co-accessibility, or eQTL measurements. A new web upload service harmonizes datasets, adds annotations, and makes it easy to explore user-provided result sets.

Availability and implementation: LocusZoom.js is open-source software under a permissive MIT license. Code and documentation are available at: https://github.com/statgen/locuszoom/. Installable packages for all versions are also distributed via NPM. Additional features are provided as standalone libraries to promote reuse. Use with your own GWAS results at https://my.locuszoom.org/.

Supplementary information: Supplementary data are available at Bioinformatics online.

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Figures

Fig. 1.
Fig. 1.
A LocusZoom.js region plot. Association summary statistics are presented as a scatter plot, with point colors indicating LD relative to the lead (most significant) variant in the region. Tick marks represent variants with significant hits in the GWAS catalog. Individual points can be labeled or annotated interactively via tooltips that expose additional information. Genes indicate introns and exons (horizontal and vertical bars)
See this image and copyright information in PMC

References

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