Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/96313
Title: TRUFA: A user-friendly web server for de novo RNA-seq analysis using cluster computing.
Author: Kornobis, Etienne
Cabellos, Luis
Aguilar, Fernando
Frías-López, Cristina
Rozas Liras, Julio A.
Marco, Jesús
Zardoya, Rafael
Keywords: Transcripció genètica
Bioinformàtica
RNA
Genetic transcription
Bioinformatics
RNA
Issue Date: 24-May-2015
Publisher: Libertas Academica
Abstract: Application of next-generation sequencing (NGS) methods for transcriptome analysis (RNA-seq) has become increasingly accessible in recent years and are of great interest to many biological disciplines including, eg, evolutionary biology, ecology, biomedicine, and computational biology. Although virtually any research group can now obtain RNA-seq data, only a few have the bioinformatics knowledge and computation facilities required for transcriptome analysis. Here, we present TRUFA (TRanscriptome User-Friendly Analysis), an open informatics platform offering a web-based interface that generates the outputs commonly used in de novo RNA-seq analysis and comparative transcriptomics. TRUFA provides a comprehensive service that allows performing dynamically raw read cleaning, transcript assembly, annotation, and expression quantification. Due to the computationally intensive nature of such analyses, TRUFA is highly parallelized and benefits from accessing high-performance computing resources. The complete TRUFA pipeline was validated using four previously published transcriptomic data sets. TRUFA's results for the example datasets showed globally similar results when comparing with the original studies, and performed particularly better when analyzing the green tea dataset. The platform permits analyzing RNA-seq data in a fast, robust, and user-friendly manner. Accounts on TRUFA are provided freely upon request at https://trufa.ifca.es.
Note: Reproducció del document publicat a: http://dx.doi.org/10.4137/EBO.S23873
It is part of: Evolutionary Bioinformatics, 2015, vol. 11, p. 97-104
Related resource: http://dx.doi.org/10.4137/EBO.S23873
URI: http://hdl.handle.net/2445/96313
ISSN: 1176-9343
Appears in Collections:Articles publicats en revistes (Genètica, Microbiologia i Estadística)

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