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BioJS-HGV Viewer: Genetic Variation Visualizer

View ORCID ProfileSaket Choudhary, View ORCID ProfileLeyla Garcia, View ORCID ProfileAndrew Nightingale, View ORCID ProfileMaria-Jesus Martin
doi: https://doi.org/10.1101/032573
Saket Choudhary
University Of Southern California;
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Leyla Garcia
European Molecular Biology laboratory - European Bioinformatics Institute (EMBL-EBI)
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Andrew Nightingale
European Molecular Biology laboratory - European Bioinformatics Institute (EMBL-EBI)
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Maria-Jesus Martin
European Molecular Biology laboratory - European Bioinformatics Institute (EMBL-EBI)
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  • For correspondence: martin@ebi.ac.uk
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Abstract

Studying the pattern of genetic variants is a primary step in deciphering the basis of biological diversity, identifying key `driver variants' that affect disease states and evolution of a species. Catalogs of genetic variants contain vast numbers of variants and are growing at an exponential rate, but lack an interactive exploratory interface. We present BioJS-HGV Viewer, a BioJS component to represent and visualize genetic variants pooled from different sources. The tool displays sequences and variants at different levels of detail, facilitating representation of variant sites and annotations in a user friendly and interactive manner. Source code for BioJS-HGV Viewer is available at: https://github.com/saketkc/biojs-genetic-variation-viewer A demo is available at: http://saketkc.github.io/biojs-genetic-variation-viewer

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted November 23, 2015.
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BioJS-HGV Viewer: Genetic Variation Visualizer
Saket Choudhary, Leyla Garcia, Andrew Nightingale, Maria-Jesus Martin
bioRxiv 032573; doi: https://doi.org/10.1101/032573
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BioJS-HGV Viewer: Genetic Variation Visualizer
Saket Choudhary, Leyla Garcia, Andrew Nightingale, Maria-Jesus Martin
bioRxiv 032573; doi: https://doi.org/10.1101/032573

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