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ATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data
BACKGROUND: In the last years, applications based on massively parallelized RNA sequencing (RNA-seq) have become valuable approaches for studying non-model species, e.g., without a fully sequenced genome. RNA-seq is a useful tool for detecting novel transcripts and genetic variations and for evaluat...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5320735/ https://www.ncbi.nlm.nih.gov/pubmed/28222698 http://dx.doi.org/10.1186/s12859-017-1494-2 |
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author | Gonzalez, Sergio Clavijo, Bernardo Rivarola, Máximo Moreno, Patricio Fernandez, Paula Dopazo, Joaquín Paniego, Norma |
author_facet | Gonzalez, Sergio Clavijo, Bernardo Rivarola, Máximo Moreno, Patricio Fernandez, Paula Dopazo, Joaquín Paniego, Norma |
author_sort | Gonzalez, Sergio |
collection | PubMed |
description | BACKGROUND: In the last years, applications based on massively parallelized RNA sequencing (RNA-seq) have become valuable approaches for studying non-model species, e.g., without a fully sequenced genome. RNA-seq is a useful tool for detecting novel transcripts and genetic variations and for evaluating differential gene expression by digital measurements. The large and complex datasets resulting from functional genomic experiments represent a challenge in data processing, management, and analysis. This problem is especially significant for small research groups working with non-model species. RESULTS: We developed a web-based application, called ATGC transcriptomics, with a flexible and adaptable interface that allows users to work with new generation sequencing (NGS) transcriptomic analysis results using an ontology-driven database. This new application simplifies data exploration, visualization, and integration for a better comprehension of the results. CONCLUSIONS: ATGC transcriptomics provides access to non-expert computer users and small research groups to a scalable storage option and simple data integration, including database administration and management. The software is freely available under the terms of GNU public license at http://atgcinta.sourceforge.net. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1494-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5320735 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-53207352017-02-24 ATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data Gonzalez, Sergio Clavijo, Bernardo Rivarola, Máximo Moreno, Patricio Fernandez, Paula Dopazo, Joaquín Paniego, Norma BMC Bioinformatics Software BACKGROUND: In the last years, applications based on massively parallelized RNA sequencing (RNA-seq) have become valuable approaches for studying non-model species, e.g., without a fully sequenced genome. RNA-seq is a useful tool for detecting novel transcripts and genetic variations and for evaluating differential gene expression by digital measurements. The large and complex datasets resulting from functional genomic experiments represent a challenge in data processing, management, and analysis. This problem is especially significant for small research groups working with non-model species. RESULTS: We developed a web-based application, called ATGC transcriptomics, with a flexible and adaptable interface that allows users to work with new generation sequencing (NGS) transcriptomic analysis results using an ontology-driven database. This new application simplifies data exploration, visualization, and integration for a better comprehension of the results. CONCLUSIONS: ATGC transcriptomics provides access to non-expert computer users and small research groups to a scalable storage option and simple data integration, including database administration and management. The software is freely available under the terms of GNU public license at http://atgcinta.sourceforge.net. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1494-2) contains supplementary material, which is available to authorized users. BioMed Central 2017-02-22 /pmc/articles/PMC5320735/ /pubmed/28222698 http://dx.doi.org/10.1186/s12859-017-1494-2 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Software Gonzalez, Sergio Clavijo, Bernardo Rivarola, Máximo Moreno, Patricio Fernandez, Paula Dopazo, Joaquín Paniego, Norma ATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data |
title | ATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data |
title_full | ATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data |
title_fullStr | ATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data |
title_full_unstemmed | ATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data |
title_short | ATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data |
title_sort | atgc transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5320735/ https://www.ncbi.nlm.nih.gov/pubmed/28222698 http://dx.doi.org/10.1186/s12859-017-1494-2 |
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