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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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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. |
format | Online Article Text |
id | pubmed-6061785 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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