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Workflow and web application for annotating NCBI BioProject transcriptome data
Author(s) -
Roberto Vera Alvarez,
Newton Medeiros Vidal,
Gina A. Garzón-Martínez,
Luz Stella Barrero,
David Landsman,
Leonardo MariñoRamírez
Publication year - 2017
Publication title -
database
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.406
H-Index - 62
ISSN - 1758-0463
DOI - 10.1093/database/bax008
Subject(s) - workflow , scripting language , annotation , computer science , world wide web , database , operating system , artificial intelligence
The volume of transcriptome data is growing exponentially due to rapid improvement of experimental technologies. In response, large central resources such as those of the National Center for Biotechnology Information (NCBI) are continually adapting their computational infrastructure to accommodate this large influx of data. New and specialized databases, such as Transcriptome Shotgun Assembly Sequence Database (TSA) and Sequence Read Archive (SRA), have been created to aid the development and expansion of centralized repositories. Although the central resource databases are under continual development, they do not include automatic pipelines to increase annotation of newly deposited data. Therefore, third-party applications are required to achieve that aim. Here, we present an automatic workflow and web application for the annotation of transcriptome data. The workflow creates secondary data such as sequencing reads and BLAST alignments, which are available through the web application. They are based on freely available bioinformatics tools and scripts developed in-house. The interactive web application provides a search engine and several browser utilities. Graphical views of transcript alignments are available through SeqViewer, an embedded tool developed by NCBI for viewing biological sequence data. The web application is tightly integrated with other NCBI web applications and tools to extend the functionality of data processing and interconnectivity. We present a case study for the species Physalis peruviana with data generated from BioProject ID 67621.

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