Differential kinetic analysis using nucleotide recoding RNA-seq and bakR

Abstract

Conventional RNA sequencing (RNA-seq) provides limited information about the kinetic mechanisms underlying changes in RNA levels. Nucleotide recoding RNA-seq methods (NR-seq; e.g., TimeLapse-seq, SLAM-seq, etc.) are widely used approaches to identify changes in RNA synthesis and degradation kinetics, yet no software exists to rigorously compare the parameters of RNA kinetics between experimental conditions. We developed bakR to address this need. bakR relies on Bayesian hierarchical modeling of NR-seq data to increase statistical power by sharing information across transcripts. Using simulated and real data, we validate bakR and demonstrate how it provides new insights into the kinetics of RNA metabolism.