Accurate quantification of spliced and unspliced transcripts for single-cell RNA sequencing with tidesurf

RNA velocity enables predicting future cellular states from single-cell RNA-sequencing (scRNA-seq) data by inferring the derivative of gene expression from separately quantified spliced and unspliced transcripts. Although the original implementation, velocyto, established the foundation for such analyses and remains widely used, it has not been updated to accommodate major advances in scRNA-seq technologies. Notably, some modern 10x Genomics protocols capture transcripts from the 5’ end rather than the 3’ end, introducing reversed transcript orientations and other protocol-specific features that velocyto is unable to correctly interpret. We demonstrate that velocyto systematically misidentifies transcript direction in 5’-sequencing data, leading to incorrect count assignments, substantial deviations in inferred velocities, and ultimately divergent biological interpretations. To address these shortcomings, we present tidesurf, a command-line tool designed for accurate quantification of spliced and unspliced molecules across both 3’- and 5’-based scRNA-seq protocols. By evaluating tidesurf on four publicly available 10x Genomics Chromium datasets and comparing it to state-of-the-art quantification approaches, we show that it reliably recovers correct transcript counts in settings where velocyto performs well (3’ chemistry) and where it fails (5’ chemistry). These results underscore that the validity of RNA velocity analyses critically depends on correct splicing-state quantification and that continued use of velocyto with 5’-sequencing data is inadvisable. Tidesurf provides a robust, up-to-date alternative that preserves the interpretability and reliability of RNA velocity across diverse experimental designs.