RiboProfiling: a Bioconductor package for standard Ribo-seq pipeline processing
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Updated: Mar 18, 2026

De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data
Published on: February 18, 2022
Alexandra Popa1, Kevin Lebrigand1, Agnes Paquet1
1Institut de Pharmacologie Mol´eculaire et Cellulaire, University Nice Sophia Antipolis and CNRS, Sophia- Antipolis, 06560, France.
Abstract:
The ribosome profiling technique (Ribo-seq) allows the selective sequencing of translated RNA regions. Recently, the analysis of genomic sequences associated to Ribo-seq reads has been widely employed to assess their coding potential. These analyses led to the identification of differentially translated transcripts under different experimental conditions, and/or ribosome pausing on codon motifs. In the context of the ever-growing need for tools analyzing Ribo-seq reads, we have developed 'RiboProfiling', a new Bioconductor open-source package. 'RiboProfiling' provides a full pipeline to cover all key steps for the analysis of ribosome footprints. This pipeline has been implemented in a single R workflow. The package takes an alignment (BAM) file as input and performs ribosome footprint quantification at a transcript level. It also identifies footprint accumulation on particular amino acids or multi amino-acids motifs. Report summary graphs and data quantification are generated automatically. The package facilitates quality assessment and quantification of Ribo-seq experiments. Its implementation in Bioconductor enables the modeling and statistical analysis of its output through the vast choice of packages available in R. This article illustrates how to identify codon-motifs accumulating ribosome footprints, based on data from Escherichia coli.
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