rhinotypeR enables reproducible rhinovirus genotype assignment from VP4/2 sequences

Martha M. Luka, Ruth Nanjala, Wafaa M. Rashed*, Winfred Gatua, Olaitan I. Awe*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

Rhinoviruses (RVs) are among the most prevalent human respiratory pathogens, yet their molecular characterization remains fragmented across analytical tools and inconsistent between studies. Current genotype assignment typically relies on sequence alignment, pairwise distance calculation, and prototype comparison. This fragmentation hinders reproducibility and scalability. Here, we present rhinotypeR, an open-source R package that provides a scriptable and transparent workflow for RV genotyping based on the VP4/2 genomic region. The package integrates multiple analytical steps; alignment, distance calculation, genotype assignment, and visualization within the Bioconductor ecosystem and applies standardized species-specific thresholds (10.5% for HRV-A/C and 9.5% for HRV-B). Using a validation dataset encompassing over 90% of known RV types, rhinotypeR reproduced pairwise genetic distances obtained with ape and MEGA X with Mantel correlation (r = 1.000, p = 0.001) and negligible numerical deviation (< 10⁻10). Approximately 80% of sequences showed complete agreement with previous genotype assignments by multiple analysts, and most remaining discrepancies occurred near the classification thresholds. Ct value distributions were broadly similar across matched, mismatched, and unassigned sequences, indicating that discrepancies were unlikely to be driven by viral load. By consolidating fragmented analytical steps into a reproducible and automated framework, rhinotypeR improves consistency in rhinovirus genotyping and supports scalable, transparent molecular surveillance. The package is freely available through Bioconductor for research and routine public health applications.
Original languageEnglish
Article number6149
Number of pages11
JournalScientific Reports
Volume16
Issue number1
DOIs
Publication statusPublished - 11 Feb 2026

Bibliographical note

Publisher Copyright:
© The Author(s) 2026.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • VP4/2 genotype
  • R package
  • Rhinovirus
  • Bioconductor
  • rhinotypeR

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