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grandR: a comprehensive package for nucleotide conversion RNA-seq data analysis

Author

Listed:
  • Teresa Rummel

    (University of Würzburg)

  • Lygeri Sakellaridi

    (University of Würzburg)

  • Florian Erhard

    (University of Würzburg
    University of Regensburg)

Abstract

Metabolic labeling of RNA is a powerful technique for studying the temporal dynamics of gene expression. Nucleotide conversion approaches greatly facilitate the generation of data but introduce challenges for their analysis. Here we present grandR, a comprehensive package for quality control, differential gene expression analysis, kinetic modeling, and visualization of such data. We compare several existing methods for inference of RNA synthesis rates and half-lives using progressive labeling time courses. We demonstrate the need for recalibration of effective labeling times and introduce a Bayesian approach to study the temporal dynamics of RNA using snapshot experiments.

Suggested Citation

  • Teresa Rummel & Lygeri Sakellaridi & Florian Erhard, 2023. "grandR: a comprehensive package for nucleotide conversion RNA-seq data analysis," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39163-4
    DOI: 10.1038/s41467-023-39163-4
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    References listed on IDEAS

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    2. Ralph S. Grand & Lukas Burger & Cathrin Gräwe & Alicia K. Michael & Luke Isbel & Daniel Hess & Leslie Hoerner & Vytautas Iesmantavicius & Sevi Durdu & Marco Pregnolato & Arnaud R. Krebs & Sébastien A., 2021. "BANP opens chromatin and activates CpG-island-regulated genes," Nature, Nature, vol. 596(7870), pages 133-137, August.
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