Abstract Using high-throughput sequencing to monitor translation in vivo, ribosome profiling can provide critical insights into the dynamics and regulation of protein synthesis in a cell. Since its introduction in 2009, this technique has played a key role in driving biological discovery, and yet it requires a rigorous computational toolkit for widespread adoption. We developed a processing pipeline and browser-based visualization, riboviz , that allows convenient exploration and analysis of riboseq datasets. In implementation, riboviz consists of a comprehensive and flexible backend analysis pipeline that allows the user to analyze their private unpublished dataset, along with a web application for comparison with previously published public datasets. Availability and implementation JavaScript and R source code and extra documentation are freely available from https://github.com/shahpr/RiboViz , while the web-application is live at www.riboviz.org .

riboviz: analysis and visualization of ribosome profiling datasets