Abstract

BackgroundRibo-seq is a popular technique for studying translation and its regulation. A Ribo-seq experiment produces a snap-shot of the location and abundance of actively translating ribosomes within a cell’s transcriptome. In practice, Ribo-seq data analysis can be sensitive to quality issues such as read length variation, low read periodicities, and contaminations with ribosomal and transfer RNA. Various software tools for data preprocessing, quality assessment, analysis, and visualization of Ribo-seq data have been developed. However, many of these tools require considerable practical knowledge of software applications, and often multiple different tools have to be used in combination with each other.ResultsWe present riboStreamR, a comprehensive Ribo-seq quality control (QC) platform in the form of an R Shiny web application. RiboStreamR provides visualization and analysis tools for various Ribo-seq QC metrics, including read length distribution, read periodicity, and translational efficiency. Our platform is focused on providing a user-friendly experience, and includes various options for graphical customization, report generation, and anomaly detection within Ribo-seq datasets.ConclusionsRiboStreamR takes advantage of the vast resources provided by the R and Bioconductor environments, and utilizes the Shiny R package to ensure a high level of usability. Our goal is to develop a tool which facilitates in-depth quality assessment of Ribo-seq data by providing reference datasets and automatically highlighting quality issues and anomalies within datasets.

Highlights

  • Ribo-seq is a popular technique for studying translation and its regulation

  • The individual tools can be accessed through tabs across the top of the application

  • Each tool consists of a toolbar, where graphical parameters can be adjusted, and an output pane, which displays the graphical output of the tool

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Summary

Introduction

Ribo-seq is a popular technique for studying translation and its regulation. A Ribo-seq experiment produces a snap-shot of the location and abundance of actively translating ribosomes within a cell’s transcriptome. Ribo-seq data analysis can be sensitive to quality issues such as read length variation, low read periodicities, and contaminations with ribosomal and transfer RNA. Various software tools for data preprocessing, quality assessment, analysis, and visualization of Ribo-seq data have been developed. Many of these tools require considerable practical knowledge of software applications, and often multiple different tools have to be used in combination with each other. The various Ribo-seq applications have given rise to several software packages and statistical methods for data processing and quality control. RiboProfiling, riboSeqR, and SystemPipeR are R packages which provide various functions for building Ribo-seq data analysis workflows and performing data QC [17,18,19]. RiboGalaxy is a web based platform which hosts various standalone tools, including

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