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Updated: Mar 8, 2026

De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data
Published on: February 18, 2022
Riborex: fast and flexible identification of differential translation from Ribo-seq data
Wenzheng Li1, Weili Wang1, Philip J Uren1
1Molecular and Computational Biology, Division of Biological Sciences, University of Southern California, Los Angeles, CA, USA.
Motivation:
Global analysis of translation regulation has recently been enabled by the development of Ribosome Profiling, or Ribo-seq, technology. This approach provides maps of ribosome activity for each expressed gene in a given biological sample. Measurements of translation efficiency are generated when Ribo-seq data is analyzed in combination with matched RNA-seq gene expression profiles. Existing computational methods for identifying genes with differential translation across samples are based on sound principles, but require users to choose between accuracy and speed.
Results:
We present Riborex, a computational tool for mapping genome-wide differences in translation efficiency. Riborex shares a similar mathematical structure with existing methods, but has a simplified implementation. Riborex directly leverages established RNA-seq analysis frameworks for all parameter estimation, providing users with a choice among robust engines for these computations. The result is a method that is dramatically faster than available methods without sacrificing accuracy.
Availability And Implementation:
https://github.com/smithlabcode/riborex.
Contact:
andrewds@usc.edu.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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