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Schlagwörter:
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Zusammenfassung:
The current revolution in sequencing technologies allows us to obtain a much more detailed picture of transcriptomes via deep RNA Sequencing (RNA-Seq). In considering the full complement of RNA transcripts that comprise the transcriptome, two important analytical questions emerge: what is the abundance of RNA transcripts and which genes or transcripts are di↵erentially expressed. In parallel with sequencing technology development, data analysis software is also constantly updated to improve accuracy and sensitivity while minimizing run times. The abundance of software programs, however, can be prohibitive and confusing for researchers to determine which to use for their RNA-Seq anlaysis. We present an open-source workbench, Oqtans, that can be integrated into the Galaxy framework that enables researchers to set up a computational pipeline for quantitative transcriptome analysis. Its distinguishing features include a modular pipeline architecture, which facilitates comparative assessment of tool and data quality. Within Oqtans, the Galaxy’s workflow achitecture enables direct comparison of several tools. Furthermore, it is straightforward to compare the performance of di↵erent programs and parameter settings on the same data and choose the best suited for the task. Oqtans analysis pipelines are easy to set up, modify, and (re-)use without significant computational skills. Oqtans integrates more than twenty sophisticated tools that perform very well compared to the state- of-the-art for transcript identification/quantification and di↵erential expression analysis. The toolsuite contains several tools developed in the R¨atsch Laboratory, but the majority of the tools were developed by other groups. In particular, we provide tools for alignment (bwa, tophat, PALMapper, . . . ), transcript prediction (cu✏inks, trinity, mTIM, . . . ) and quantitative analyses (DESeq, rDi↵, rQuant, . . . ). In addition, we provide tools for alignment filtering (RNA-geeq toolbox), GFF file processing (GFF toolbox) and tools for predictive sequence analysis (easySVM, ASP, ARTS, . . . ). See http://oqtans.org/tools for more details on included tools. Oqtans is integrated into the Galaxy server http://galaxy.raetschlab.org maintained by the R¨atsch Laboratory. It is also available as source code in a public github repository http://bioweb.me/oqtans/ git and as an Amazon Machine Image for the AWS cloud environment (instructions available at http: //oqtans.org). Finally, Oqtans sets a new standard in terms of reproducibility and builds upon Galaxys features to facilitate persistent storage, exchange, and documentation of intermediate results and analysis workflows.
