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. 2018 Aug 1;34(15):2651-2653.
doi: 10.1093/bioinformatics/bty106.

EPIC-CoGe: managing and analyzing genomic data

Andrew D L Nelson  1 , Asher K Haug-Baltzell  1 , Sean Davey  1 , Brian D Gregory  2 , Eric Lyons  1
Affiliations

EPIC-CoGe: managing and analyzing genomic data

Andrew D L Nelson et al. Bioinformatics. .

Abstract

Summary: The EPIC-CoGe browser is a web-based genome visualization utility that integrates the GMOD JBrowse genome browser with the extensive CoGe genome database (currently containing over 30 000 genomes). In addition, the EPIC-CoGe browser boasts many additional features over basic JBrowse, including enhanced search capability and on-the-fly analyses for comparisons and analyses between all types of functional and diversity genomics data. There is no installation required and data (genome, annotation, functional genomic and diversity data) can be loaded by following a simple point and click wizard, or using a REST API, making the browser widely accessible and easy to use by researchers of all computational skill levels. In addition, EPIC-CoGe and data tracks are easily embedded in other websites and JBrowse instances.

Availability and implementation: EPIC-CoGe Browser is freely available for use online through CoGe (https://genomevolution.org). Source code (MIT open source) is available: https://github.com/LyonsLab/coge.

Supplementary information: Supplementary data are available at Bioinformatics online.

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References

    1. Buels R. et al. (2016) JBrowse: a dynamic web platform for genome visualization and analysis. Genome Biol., 17, 66.. - PMC - PubMed
    1. Grover J.W. et al. (2017) CoGe LoadExp+: a web-based suite that integrates next-generation sequencing data analysis workflows and visualization. Plant Direct, 1, 343. - PMC - PubMed
    1. Lyons E., Freeling M. (2008) How to usefully compare homologous plant genes and chromosomes as DNA sequences. Plant J. Cell Mol. Biol., 53, 661–673. - PubMed

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