RNAmodR.RiboMethSeq: Detecting 2′-O Methylations from RiboMethSeq Data

RNAmodR.RiboMethSeq is a Bioconductor package designed for the detection of 2′-O methylations in RNA using experimental data generated with the RiboMethSeq protocol. Built on top of the core RNAmodR framework, the package enables researchers to identify characteristic modification patterns in high-throughput sequencing datasets, providing a streamlined workflow for RNA modification analysis.

The released version belongs to Bioconductor 3.23 and offers tools for analyzing sequencing data with reproducible and well-documented methods. It is particularly relevant to bioinformatics researchers working with RNA epigenetics and transcriptome-wide modification studies.

Overview of RNAmodR.RiboMethSeq

RNAmodR.RiboMethSeq extends the functionality of RNAmodR to specifically support the detection of 2′-O methylated nucleotides. The package processes data generated by the RiboMethSeq protocol and identifies modification signatures through established computational approaches.

Key highlights include:

• Detection of RNA 2′-O methylation sites.
• Integration with the RNAmodR framework.
• Support for high-throughput sequencing datasets.
• Visualization capabilities through Bioconductor packages.
• Compatibility with modern R environments.

The current release is version 1.26.0, which has been available in Bioconductor since version 3.10 (R 3.6).

Main Features

RNAmodR.RiboMethSeq focuses on several essential aspects of RNA modification analysis:

Detection of 2′-O Methylation

The package implements methods tailored to RiboMethSeq-generated sequencing data, enabling accurate identification of 2′-O methylation events.

High-Throughput Data Analysis

Built for next-generation sequencing workflows, RNAmodR.RiboMethSeq can handle large datasets and leverage the underlying RNAmodR architecture for pattern detection and annotation.

Visualization Support

Several Bioconductor packages contribute to visualization and genomic data representation, including:

• Gviz
• GenomicRanges
• IRanges
• S4Vectors
• BiocGenerics

These components help researchers inspect modification patterns and genomic regions efficiently.

Authors and Maintenance

RNAmodR.RiboMethSeq was developed by:

• Felix G.M. Ernst (author and maintainer)
• Denis L.J. Lafontaine (contributor and founder)

The package is actively maintained, ensuring compatibility with recent Bioconductor and R releases.

Installation

To install RNAmodR.RiboMethSeq, start R version 4.6 and run:

R

if (!require(“BiocManager”, quietly = TRUE))
install.packages(“BiocManager”)

BiocManager::install(“RNAmodR.RiboMethSeq”)

Users running older R versions should refer to the corresponding Bioconductor release compatible with their environment.

Documentation and Resources

Once installed, package documentation can be accessed using:

R

browseVignettes(“RNAmodR.RiboMethSeq”)

Available resources include:

• HTML vignette
• R script examples
• Reference manual in PDF format
• NEWS changelog
• Bioconductor support forum

These materials help users understand package workflows and integrate RNAmodR.RiboMethSeq into broader RNA sequencing pipelines.

Software Requirements

The package depends on:

• R version 4.0 or later
• RNAmodR version 1.5.3 or newer

Imported packages include:

• methods
• S4Vectors
• BiocGenerics
• IRanges
• GenomicRanges
• Gviz

Additional suggested packages include:

• BiocStyle
• knitr
• rmarkdown
• testthat
• rtracklayer
• Seqinfo
• RNAmodR.Data

Technical Information

Package Archives and Distribution

RNAmodR.RiboMethSeq is available through multiple distributions:

• Source package (.tar.gz)
• Windows binaries (.zip)
• macOS binaries (.tgz)
• Git source repository
• Bioconductor package browser

These distribution formats simplify deployment across different operating systems and computational environments.

Use Cases in RNA Epigenetics

Researchers studying RNA modifications can employ RNAmodR.RiboMethSeq for:

• Mapping 2′-O methylation sites.
• Investigating RNA epigenetic mechanisms.
• Analyzing transcriptome-wide sequencing datasets.
• Building reproducible bioinformatics workflows.
• Integrating modification analyses with other Bioconductor tools.

Related Tools

For broader RNA modification analysis, users may also explore:

• RNAmodR
• RNAmodR.Data
• GenomicRanges
• Gviz
• rtracklayer

These packages complement RNAmodR.RiboMethSeq and facilitate comprehensive RNA sequencing analyses.

Conclusion

RNAmodR.RiboMethSeq provides a specialized framework for detecting 2′-O methylations from RiboMethSeq experiments. By leveraging the RNAmodR ecosystem and Bioconductor infrastructure, it offers researchers a reproducible and scalable solution for analyzing RNA modification patterns in high-throughput sequencing data.

Researchers interested in RNA epigenetics and transcriptomic modifications can benefit from the package’s documentation, visualization capabilities, and integration with established Bioconductor workflows. Explore additional RNA analysis tools and share your experiences with RNAmodR.RiboMethSeq to support the growing community of RNA modification research.

References

Ernst, F. G. M., & Lafontaine, D. L. J. (2026). RNAmodR.RiboMethSeq: Detection of 2′-O methylations by RiboMethSeq. Bioconductor, Version 1.26.0.

Bioconductor. (2026). RNAmodR.RiboMethSeq Package Documentation. Bioconductor Release 3.23.

Bioconductor Project. (2026). RNAmodR and associated packages for RNA modification analysis. Available through the Bioconductor ecosystem.