Riborex
Computational Tool
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General Information
DescriptionFast and flexible identification of differential translation from Ribo-seq data
Homepagehttps://github.com/smithlabcode/riborex
Publications
Riborex: fast and flexible identification of differential translation from Ribo-seq data
Wenzheng Li; Weili Wang; Philip J. Uren; Luiz O. F. Penalva; Andrew D. Smith
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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