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Updated: Aug 23, 2025
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De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data
Published on: February 18, 2022
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RP-REP Ribosomal Profiling Reports: an open-source cloud-enabled framework for reproducible ribosomal profiling data
Travis L Jensen1, William F Hooper1, Sami R Cherikh1
1The Emmes Company, 401 North Washington Street, Suite 700, Rockville, MD 20850, USA.
F1000Research
|October 27, 2022
Summary
Ribosomal Profiling Reports (RP-REP) is new software for analyzing protein synthesis data. It simplifies complex ribosomal profiling and RNA-Seq analysis, enabling biomarker discovery and gene response detection.
Area of Science:
- Genomics
- Computational Biology
- Molecular Biology
Background:
- Ribosomal profiling measures global protein synthesis, crucial for biomarker discovery.
- Analyzing this data requires specialized preprocessing and statistical methods.
- Existing tools lack comprehensive, user-friendly solutions for end-to-end analysis.
Purpose of the Study:
- To introduce Ribosomal Profiling Reports (RP-REP), an open-source, cloud-enabled software.
- To provide a streamlined pipeline for gene-level ribosomal profiling and RNA-Seq analysis.
- To facilitate biomarker discovery and the identification of treatment-responsive genes.
Main Methods:
- RP-REP software executed on AWS or Ubuntu Linux servers.
- Analysis of FASTQ files from local, AWS S3, or SRA storage.
- Automated steps: RNA filtering, footprint enrichment, alignment, quantification, QC, normalization, visualization, differential translation analysis.
Main Results:
- RP-REP successfully processed ribosomal profiling and RNA-Seq data.
- The software generated comprehensive PDF reports and publication-ready figures.
- Demonstrated utility via a dengue virus infection study case.
Conclusions:
- RP-REP offers a powerful, accessible solution for analyzing ribosomal profiling data.
- The software simplifies complex analyses, aiding in biological insights.
- RP-REP supports biomarker discovery and understanding gene responses to treatments.
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