Halfpipe: a tool for analyzing metabolic labeling RNA-seq data to quantify RNA half-lives

Abstract

We introduce Halfpipe, a tool for analyzing RNA-seq data from metabolic RNA labeling experiments. Its main features are the absolute quantification of 4sU-labeling-induced T>C conversions in the data as generated by SLAM-seq, calculating the proportion of newly synthesized transcripts, and estimating subcellular RNA half-lives. Halfpipe excels at correcting critical biases caused by typically low labeling efficiency. We measure and compare the RNA metabolism in the G1 phase and during the mitosis of synchronized human cells. We find that RNA half-lives of constantly expressed RNAs are similar in mitosis and G1 phase, suggesting that RNA stability of those genes is constant throughout the cell cycle. Our estimates correlate well with literature values and with known RNA sequence features. Halfpipe is freely available at https://github.com/IMSBCompBio/Halfpipe