satuRn: Scalable analysis of differential transcript usage for bulk and single-cell RNA-sequencing applications
Jeroen Gilis, Kristoffer Vitting‐Seerup, Koen Van den Berge, Lieven Clement
Abstract
<ns4:p> Alternative splicing produces multiple functional transcripts from a single gene. Dysregulation of splicing is known to be associated with disease and as a hallmark of cancer. Existing tools for differential transcript usage (DTU) analysis either lack in performance, cannot account for complex experimental designs or do not scale to massive scRNA-seq data. We introduce <ns4:italic>satuRn</ns4:italic> , a fast and flexible quasi-binomial generalized linear modelling framework that is on par with the best performing DTU methods from the bulk RNA-seq realm, while providing good false discovery rate control, addressing complex experimental designs and scaling to scRNA-seq applications. </ns4:p>