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BMC Genomics. 2018 Nov 8;19(1):809. doi: 10.1186/s12864-018-5166-z.

RIVET: comprehensive graphic user interface for analysis and exploration of genome-wide translatomics data.

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Department of Microbiology, New York University School of Medicine, New York, 10016, USA.
Department of Microbiology, New York University School of Medicine, New York, 10016, USA.
Department of Medicine, Department of Translational Medicine, New York University School of Medicine, New York, 10016, USA.



Translatomics data, particularly genome-wide ribosome profiling and polysome profiling, provide multiple levels of gene regulatory information that can be used to assess general transcription and translation, as well translational efficiency. The increasing popularity of these techniques has resulted in multiple algorithms to detect translational regulation, typically distributed in the form of command line tools that require a basic level of programming ability. Additionally, due to the static nature of current software, dynamic transcriptional and translational comparative analysis cannot be adequately achieved. In order to streamline hypothesis generation, investigators must have the ability to manipulate and interact with their data in real-time.


To address the lack of integration in current software, we introduce RIVET, Ribosomal Investigation and Visualization to Evaluate Translation, an R shiny based graphical user interface for translatomics data exploration and differential analysis. RIVET can analyze either microarray or RNA sequencing data from polysome profiling and ribosome profiling experiments. RIVET provides multiple choices for statistical analysis as well as integration of transcription, translation, and translational efficiency data analytics and the ability to visualize all results dynamically.


RIVET is a user-friendly tool designed for bench scientists with little to no programming background. RIVET facilitates the data analysis of translatomics data allowing for dynamic generation of results based on user-defined inputs and publication ready visualization. We expect RIVET will allow for scientists to efficiently make more comprehensive data observations that will lead to more robust hypothesis regarding translational regulation.


Differential expression; Polysome profiling; R shiny; Ribosome profiling; Translational efficiency; Translational regulation

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