HRIBO: high-throughput analysis of bacterial ribosome profiling data

Bioinformatics. 2021 Aug 4;37(14):2061-2063. doi: 10.1093/bioinformatics/btaa959.


Motivation: Ribosome profiling (Ribo-seq) is a powerful approach based on deep sequencing of cDNA libraries generated from ribosome-protected RNA fragments to explore the translatome of a cell, and is especially useful for the detection of small proteins (50-100 amino acids) that are recalcitrant to many standard biochemical and in silico approaches. While pipelines are available to analyze Ribo-seq data, none are designed explicitly for the automatic processing and analysis of data from bacteria, nor are they focused on the discovery of unannotated open reading frames (ORFs).

Results: We present HRIBO (High-throughput annotation by Ribo-seq), a workflow to enable reproducible and high-throughput analysis of bacterial Ribo-seq data. The workflow performs all required pre-processing and quality control steps. Importantly, HRIBO outputs annotation-independent ORF predictions based on two complementary bacteria-focused tools, and integrates them with additional feature information and expression values. This facilitates the rapid and high-confidence discovery of novel ORFs and their prioritization for functional characterization.

Availability and implementation: HRIBO is a free and open source project available under the GPL-3 license at:

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Bacteria / genetics
  • High-Throughput Nucleotide Sequencing
  • Horses
  • Open Reading Frames
  • Protein Biosynthesis*
  • RNA, Ribosomal
  • Ribosomes* / genetics
  • Ribosomes* / metabolism


  • RNA, Ribosomal