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.
CITATION STYLE
Li, W., Wang, W., Uren, P. J., Penalva, L. O. F., & Smith, A. D. (2017). Riborex: Fast and flexible identification of differential translation from Ribo-seq data. Bioinformatics, 33(11), 1735–1737. https://doi.org/10.1093/bioinformatics/btx047
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