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EPIC-CoGe: managing and analyzing genomic data

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, includ...

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Autores principales: Nelson, Andrew D L, Haug-Baltzell, Asher K, Davey, Sean, Gregory, Brian D, Lyons, Eric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6061785/
https://www.ncbi.nlm.nih.gov/pubmed/29474529
http://dx.doi.org/10.1093/bioinformatics/bty106
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author Nelson, Andrew D L
Haug-Baltzell, Asher K
Davey, Sean
Gregory, Brian D
Lyons, Eric
author_facet Nelson, Andrew D L
Haug-Baltzell, Asher K
Davey, Sean
Gregory, Brian D
Lyons, Eric
author_sort Nelson, Andrew D L
collection PubMed
description 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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spelling pubmed-60617852018-08-07 EPIC-CoGe: managing and analyzing genomic data Nelson, Andrew D L Haug-Baltzell, Asher K Davey, Sean Gregory, Brian D Lyons, Eric Bioinformatics Applications Notes 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. Oxford University Press 2018-08-01 2018-02-20 /pmc/articles/PMC6061785/ /pubmed/29474529 http://dx.doi.org/10.1093/bioinformatics/bty106 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Applications Notes
Nelson, Andrew D L
Haug-Baltzell, Asher K
Davey, Sean
Gregory, Brian D
Lyons, Eric
EPIC-CoGe: managing and analyzing genomic data
title EPIC-CoGe: managing and analyzing genomic data
title_full EPIC-CoGe: managing and analyzing genomic data
title_fullStr EPIC-CoGe: managing and analyzing genomic data
title_full_unstemmed EPIC-CoGe: managing and analyzing genomic data
title_short EPIC-CoGe: managing and analyzing genomic data
title_sort epic-coge: managing and analyzing genomic data
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6061785/
https://www.ncbi.nlm.nih.gov/pubmed/29474529
http://dx.doi.org/10.1093/bioinformatics/bty106
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