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BEST: Barcode Enabled Sequencing of Tetrads
Published on: May 1, 2014
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rhinotypeR enables reproducible rhinovirus genotype assignment from VP4/2 sequences
Martha M Luka1, Ruth Nanjala2, Wafaa M Rashed3,4
1School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, G12 8QQ, UK.
Scientific Reports
|February 11, 2026
Summary
Rhinovirus (RV) genotyping is now more consistent and scalable with rhinotypeR, an R package automating sequence analysis. This tool improves reproducibility for molecular surveillance of these common respiratory pathogens.
Area of Science:
- Virology
- Bioinformatics
- Computational Biology
Background:
- Rhinoviruses (RVs) are common respiratory pathogens, but their genetic typing is inconsistent across studies.
- Current methods for RV genotyping are fragmented, hindering reproducibility and scalability.
Purpose of the Study:
- To introduce rhinotypeR, an open-source R package for standardized and automated rhinovirus genotyping.
- To provide a reproducible and transparent workflow for molecular surveillance of RVs.
Main Methods:
- Developed rhinotypeR, an R package integrating alignment, distance calculation, genotype assignment, and visualization.
- Applied standardized, species-specific thresholds for genotype assignment (10.5% for HRV-A/C, 9.5% for HRV-B).
- Validated the package using a dataset covering over 90% of known RV types.
Main Results:
- rhinotypeR accurately reproduced genetic distances with high correlation (r=1.000, p=0.001) compared to existing tools.
- Achieved 80% agreement with previous genotype assignments, with discrepancies mainly near classification thresholds.
- Viral load (Ct values) did not appear to drive assignment discrepancies.
Conclusions:
- rhinotypeR offers a consolidated, automated framework for consistent rhinovirus genotyping.
- The package enhances reproducibility and scalability for molecular surveillance of RVs.
- rhinotypeR is available via Bioconductor for research and public health applications.
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