Abstract
Ribosome profiling has emerged as a powerful technique to study mRNA translation. Ribosome profiling has the potential to determine the relative quantities and locations of ribosomes on mRNA genome wide. Taking full advantage of this approach requires accurate measurement of ribosome locations. However, experimental inconsistencies often obscure the positional information encoded in ribosome profiling data. Here, we describe the Ribodeblur pipeline, a computational analysis tool that uses a maximum likelihood framework to infer ribosome positions from heterogeneous datasets. Ribodeblur is simple to install, and can be run on an average modern Mac or Linux-based laptop. We detail the process of applying the pipeline to high-coverage ribosome profiling data in yeast, and discuss important considerations for potential extension to other organisms.