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pulseR: Versatile computational analysis of RNA turnover from metabolic labeling experiments
Alexey Uvarovskii1,2, Christoph Dieterich1,2
1Section of Bioinformatics and Systems Cardiology, Department of Internal Medicine III, Klaus Tschira Institute for Integrative Computational Cardiology, University Hospital Heidelberg.
Motivation:
Metabolic labelling of RNA is a well-established and powerful method to estimate RNA synthesis and decay rates. The pulseR R package simplifies the analysis of RNA-seq count data that emerge from corresponding pulse-chase experiments.
Results:
The pulseR package provides a flexible interface and readily accommodates numerous different experimental designs. To our knowledge, it is the first publicly available software solution that models count data with the more appropriate negative-binomial model. Moreover, pulseR handles labelled and unlabelled spike-in sets in its workflow and accounts for potential labeling biases (e.g. number of uridine residues).
Availability And Implementation:
The pulseR package is freely available at https://github.com/dieterich-lab/pulseR under the GPLv3.0 licence.
Contact:
a.uvarovskii@uni-heidelberg.de or christoph.dieterich@uni-heidelberg.de.
Supplementary Information:
Supplementary data are available at Bioinformatics online.