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

Research output: Contribution to journalArticlepeer-review

63 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)1735-1737
Number of pages3
JournalBioinformatics
Volume33
Issue number11
DOIs
StatePublished - Jun 1 2017

ASJC Scopus subject areas

  • Computational Mathematics
  • Molecular Biology
  • Biochemistry
  • Statistics and Probability
  • Computer Science Applications
  • Computational Theory and Mathematics

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