Accurate quantification of spliced and unspliced transcripts for single-cell RNA sequencing with tidesurf
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Motivation
Single-cell RNA sequencing (scRNA-seq) allows for the detailed analysis of dynamic cellular processes. In particular, this has been enabled by the estimation of RNA velocity, the derivative of gene expression, from separate count matrices for different splice states, which provides information about a cell’s immediate future even in snapshot data. Useful velocity estimates strongly depend on accurate counts for spliced and unspliced transcripts. Velocyto remains the standard tool for spliced and unspliced mRNA molecule quantification. However, despite considerable advances in scRNA-seq protocols, velocyto has not been updated to account for peculiarities of new protocols, such as popular approaches based on 5’ chemistry.
Results
To address this shortcoming, we present tidesurf, a command line tool for the quantification of spliced and unspliced transcript molecules from scRNA-seq libraries. Employing it on four different publicly available 10x Genomics Chromium datasets, we show the accuracy on various datasets generated with either 3’ or 5’ chemistry, whereas velocyto’s results are highly erroneous for the latter. Considering broader applicability, our results highlight tidesurf as a potential replacement for velocyto.
Availability and implementation
A Python implementation of tidesurf is available from PyPI and at github.com/janschleicher/tidesurf . Code for reproducing the analyses is available at github.com/janschleicher/tidesurf projects.
