Your browser doesn't support javascript.
loading
EPIC-CoGe: managing and analyzing genomic data.
Nelson, Andrew D L; Haug-Baltzell, Asher K; Davey, Sean; Gregory, Brian D; Lyons, Eric.
Afiliación
  • Nelson ADL; BIO5 Institute, School of Plant Sciences, University of Arizona, Tucson, AZ, USA.
  • Haug-Baltzell AK; BIO5 Institute, School of Plant Sciences, University of Arizona, Tucson, AZ, USA.
  • Davey S; BIO5 Institute, School of Plant Sciences, University of Arizona, Tucson, AZ, USA.
  • Gregory BD; Department of Biology, University of Pennsylvania, Philadelphia, PA, USA.
  • Lyons E; BIO5 Institute, School of Plant Sciences, University of Arizona, Tucson, AZ, USA.
Bioinformatics ; 34(15): 2651-2653, 2018 08 01.
Article en En | MEDLINE | ID: mdl-29474529
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Genoma / Análisis de Secuencia de ADN / Anotación de Secuencia Molecular / Visualización de Datos Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Genoma / Análisis de Secuencia de ADN / Anotación de Secuencia Molecular / Visualización de Datos Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos