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 language | English (US) |
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Pages (from-to) | 1735-1737 |
Number of pages | 3 |
Journal | Bioinformatics |
Volume | 33 |
Issue number | 11 |
DOIs | |
State | Published - Jun 1 2017 |
ASJC Scopus subject areas
- Computational Mathematics
- Molecular Biology
- Biochemistry
- Statistics and Probability
- Computer Science Applications
- Computational Theory and Mathematics