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ModSeqR: An R package for efficient analysis of modified nucleotide data

Zimmerman, H. E.; Moore, J.; Miller, R. H.; Stirland, I.; Jenkins, A.; Saito, E.; Jenkins, T.; Hill, J. T.

2026-02-11 bioinformatics
10.1101/2025.11.10.687705 bioRxiv
Show abstract

DNA methylation regulates a wide range of biological processes, including gene expression, disease progression, and cell identity. Long-read technologies now enable more comprehensive and accurate methylome analyses than ever before, but they are hindered by the computational resources needed to analyze the massive datasets. Here, we present the CH3 file format, which aids data storage and transfer by reducing file sizes by more than 95%, and the ModSeqR R package, which builds on the CH3 format and a database backend to enable a broad range of epigenetic analyses. Together, these tools enable high-throughput methylation analysis while minimizing computational resource requirements.

Published in BMC Genomics (predicted rank #12) · training set

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