Abstract
Single-cell RNA sequencing (scRNA-seq) facilitates the study of transcriptome diversity in individual cells. Yet, many existing methods lack sensitivity and accuracy. Here we introduce SCALPEL, a Nextflow-based tool to quantify and characterize transcript isoforms from standard 3’ scRNA-seq data. Using syn- thetic data, SCALPEL demonstrates higher sensitivity and specificity compared to other tools. In real datasets, SCALPEL predictions have a high agreement with other tools and can be experimentally validated. The use of SCALPEL on real datasets reveals novel cell populations undetectable using single-cell gene expression data, confirms known 3’ UTR length changes during cell differ- entiation, and identifies cell-type specific miRNA signatures regulating isoform expression. Additionally, we show that SCALPEL improves isoform quantifi- cation using paired long- and short-read scRNA-seq data. Overall, SCALPEL expands the current scRNA-seq toolkit to explore post-transcriptional gene regulation across species, tissues, and technologies, advancing our under- standing of gene regulatory mechanisms at the single-cell level.
