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

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• Ribosome profiling has advanced understanding of the translatome, revealing numerous alternative open reading frames (ORFs).
• Current ORF detection tools lack visual inspection capabilities crucial for validation and prediction of translation.
• Novel ORFs include out-of-frame, overlapping, upstream, downstream, and non-canonical start codon variants.

Purpose of the Study:

• To present InspectorORF, an R package for visualizing ribosome profiling and RNA sequencing reads.
• To facilitate the validation and prediction of novel ORFs by enabling visual inspection of translation data.
• To integrate diverse evidence, including proteomics and long-read sequencing, for robust ORF validation.

Main Methods:

• Development of InspectorORF, an R package for data visualization.
• Integration of ribosome profiling and RNA sequencing reads for comparative analysis.
• Customizable plotting options to include proteomic and long-read sequencing data.

Main Results:

• InspectorORF enables the discrimination between transcriptional and translational signals.
• The package facilitates the validation of predicted novel ORFs through integrated data visualization.
• Complementary evidence from proteomics and long-read sequencing can be incorporated for enhanced validation.

Conclusions:

• InspectorORF provides a valuable tool for researchers studying translation and novel ORF discovery.
• Visual inspection of ribosome profiling data is essential for accurate ORF validation.
• Integrated analysis of multi-omics data improves the reliability of novel ORF identification.