Riborex: fast and flexible identification of differential translation from Ribo-seq data
Author(s) -
Wenzheng Li,
Weili Wang,
Philip J. Uren,
Luiz O. F. Penalva,
Andrew D. Smith
Publication year - 2017
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btx047
Subject(s) - computer science , translation (biology) , ribosome profiling , identification (biology) , computation , data mining , profiling (computer programming) , rna seq , differential (mechanical device) , computational biology , algorithm , gene , messenger rna , gene expression , biology , genetics , programming language , botany , transcriptome , engineering , aerospace engineering
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.
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