Riborex: fast and flexible identification of differential translation from Ribo-seq data.
BACKGROUND
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.


METHODS
https://github.com/smithlabcode/riborex.


BACKGROUND
andrewds@usc.edu.


BACKGROUND
Supplementary data are available at Bioinformatics online.
Molecular and Computational Biology, Division of Biological Sciences, University of Southern California, Los Angeles, CA, USA.
Wenzheng
W
Li
Molecular and Computational Biology, Division of Biological Sciences, University of Southern California, Los Angeles, CA, USA.
Weili
W
Wang
Molecular and Computational Biology, Division of Biological Sciences, University of Southern California, Los Angeles, CA, USA.
Philip J
PJ
Uren
Department of Cellular and Structural Biology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.|Children's Cancer Research Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
Luiz O F
LOF
Penalva
Molecular and Computational Biology, Division of Biological Sciences, University of Southern California, Los Angeles, CA, USA.
Andrew D
AD
Smith
D000818:Animals; D019295:Computational Biology / Q000379:methods; D006801:Humans; D051379:Mice; D014176:Protein Biosynthesis; D012270:Ribosomes / Q000378:metabolism*; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software; D059467:Transcriptome