Ake, FranzSchilling, MarcelFernandez Moya, Sandra M.Jaya Ganesh, AkshayGutiérrez Franco, AnaLi, LeiPlass, Mireya2025-08-282025-08-282025-12-012041-1723https://hdl.handle.net/2445/222802Single-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 synthetic 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 differentiation, and identifies cell-type specific miRNA signatures regulating isoform expression. Additionally, we show that SCALPEL improves isoform quantification 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 understanding of gene regulatory mechanisms at the single-cell level.17 p.application/pdfengcc-by-nc-nd (c) Ake, F. et al., 2025https://creativecommons.org/licenses/by-nc-nd/4.0/Expressió gènicaMicro RNAsAnimalsRatolins (Animals de laboratori)Gene expressionMicroRNAsAnimalsMice (Laboratory animals)info:eu-repo/semantics/article7597212025-08-28info:eu-repo/semantics/openAccess40640129