Title | ATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data. |
Publication Type | Journal Article |
Year of Publication | 2017 |
Authors | Gonzalez, S, Clavijo, B, Rivarola, M, Moreno, P, Fernandez, P, Dopazo, J, Paniego, N |
Journal | BMC Bioinformatics |
Volume | 18 |
Issue | 1 |
Pagination | 121 |
Date Published | 2017 Feb 22 |
ISSN | 1471-2105 |
Keywords | Animals; Databases, Genetic; Gene Expression Profiling; High-Throughput Nucleotide Sequencing; Internet; Sequence Analysis, RNA; Transcriptome; User-Computer Interface |
Abstract | 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 . |
DOI | 10.1186/s12859-017-1494-2 |
Alternate Journal | BMC Bioinformatics |
PubMed ID | 28222698 |
PubMed Central ID | PMC5320735 |