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grandR: a comprehensive package for nucleotide conversion sequencing data analysis

Teresa Rummel, Lygeri Sakellaridi, View ORCID ProfileFlorian Erhard
doi: https://doi.org/10.1101/2022.09.12.507665
Teresa Rummel
1Institute for Virology and Immunobiology, Versbacher Str. 7, 97078 Würzburg, Germany
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Lygeri Sakellaridi
1Institute for Virology and Immunobiology, Versbacher Str. 7, 97078 Würzburg, Germany
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Florian Erhard
1Institute for Virology and Immunobiology, Versbacher Str. 7, 97078 Würzburg, Germany
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  • ORCID record for Florian Erhard
  • For correspondence: Florian.Erhard@uni-wuerzburg.de
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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. We here 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.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/erhard-lab/grandR-manuscript/releases/tag/init.submission

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted September 15, 2022.
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grandR: a comprehensive package for nucleotide conversion sequencing data analysis
Teresa Rummel, Lygeri Sakellaridi, Florian Erhard
bioRxiv 2022.09.12.507665; doi: https://doi.org/10.1101/2022.09.12.507665
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grandR: a comprehensive package for nucleotide conversion sequencing data analysis
Teresa Rummel, Lygeri Sakellaridi, Florian Erhard
bioRxiv 2022.09.12.507665; doi: https://doi.org/10.1101/2022.09.12.507665

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