Ward, E.L. orcid.org/0000-0002-7175-8148, Birds, I., O’Connell, M.J. et al. (2 more authors) (2026) InspectorORF: a tool for visualising Ribo-Seq and additional genomic or transcriptomic data. Bioinformatics Advances, 6 (1). vbag031. ISSN: 2635-0041
Abstract
Motivation
The advent of ribosome profiling (an adaptation of RNA sequencing) to determine the translatome, has led to a huge improvement in our understanding of what parts of the transcriptome are translated. Many alternative open reading frames (ORFs) are now regularly being detected such as out-of-frame, overlapping, upstream or downstream reading frames, and alternative reading frames using non-canonical start codons. Various tools have been developed for the detection of such novel ORFs, but they lack the capacity to visually inspect reads—an important aspect of validation and prediction of translation.
Results
The integrated and visualisation of ribosome profiling and RNA sequencing reads enables discrimination between transcriptional and translational signals, facilitating validation of predicted novel open reading frames. Furthermore, the inclusion of complementary evidence such as proteomic and long-read sequencing enables further validation of predicted novel open reading frames.
Availability and implementation
Here, we present, InspectorORF (https://www.github.com/aylz83/inspectorORF), an R package that readily plots ribosome profiling reads, alongside RNA sequencing reads across transcripts and/or ORFs. Additionally, custom information can be plotted including data from additional conditions and samples, proteomic analyses and reads from long-read sequencing.
Metadata
| Item Type: | Article |
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| Editors: |
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| Copyright, Publisher and Additional Information: | © The Author(s) 2026. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Biology (Leeds) The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Molecular and Cellular Biology (Leeds) |
| Date Deposited: | 27 Feb 2026 12:46 |
| Last Modified: | 27 Feb 2026 12:46 |
| Status: | Published |
| Publisher: | Oxford University Press (OUP) |
| Identification Number: | 10.1093/bioadv/vbag031 |
| Related URLs: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:238467 |
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