Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.11.10.377572v1?rss=1 Authors: Olivieri, J. E., Dehghannasiri, R., Salzman, J. Abstract: To date, the field of single-cell genomics has viewed robust splicing analysis as completely out of reach in droplet-based platforms, preventing biological discovery of single-cell regulated splicing. Here, we introduce a novel, robust, and computationally efficient statistical method, the Splicing Z Score (SZS), to detect differential alternative splicing in single cell RNA-Seq technologies including 10x Chromium. We applied the SZS to primary human cells to discover new regulated, cell type-specific splicing patterns. Illustrating the power of the SZS method, splicing of a small set of genes has high predictive power for tissue compartment in the human lung, and the SZS identifies un-annotated, conserved splicing regulation in the human spermatogenesis. The SZS is a method that can rapidly identify regulated splicing events from single cell data and prioritize genes predicted to have functionally significant splicing programs. Copy rights belong to original authors. Visit the link for more info