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bioRxiv · 10.1101/2022.09.12.507665

grandR: a comprehensive package for nucleotide conversion sequencing data analysis

Rummel, T.·Sakellaridi, L.·Erhard, F.
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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.

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Rummel, T., Sakellaridi, L., Erhard, F.. 2022-09-15. grandR: a comprehensive package for nucleotide conversion sequencing data analysis. https://doi.org/10.1101/2022.09.12.507665

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