# InspectorORF: a tool for visualizing Ribo-Seq and additional genomic or transcriptomic data

## TL;DR

InspectorORF is a new tool that helps scientists visualize ribosome profiling and other genomic data to better understand which parts of RNA are being translated.

## Contribution

InspectorORF introduces a visualization tool for integrating ribosome profiling and RNA sequencing data to validate novel open reading frames.

## Key findings

- InspectorORF allows visualization of ribosome profiling and RNA sequencing reads to distinguish translational from transcriptional signals.
- The tool supports integration of proteomic and long-read sequencing data for enhanced validation of novel ORFs.
- InspectorORF is implemented as an R package and is publicly available for use.

## Abstract

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.

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.

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.