Ribo-seq is a popular technique for studying translation and its regulation. Various software tools for data preprocessing, quality assessment, analysis, and visualization of Ribo-seq data have been developed. However, many of them are inaccessible to users without a thorough practical knowledge of software applications, and often multiple different tools have to be used in combination with each other. Here, we 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. The platform's environment is centered on providing a user-friendly experience, and includes numerous options for graphical customization and report generation. In practice, Ribo-seq data analysis can be sensitive to data quality issues such as read length variation, low read periodicities, and contaminations with ribosomal and transfer RNA. What constitutes ‘high quality’ data is often unclear. Our goal is to develop novel functionality to automatically highlight quality issues and anomalies in the data. This NSF-supported project is performed in collaboration with Jose Alonso, Anna Stepanova, Serina Mazzoni-Putman, and Cranos Williams.