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Updated: Jan 16, 2026

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
Published on: June 24, 2021
ScASplicer: An interactive shiny/R application for alternative splicing analysis of single-cell sequencing
Pengwei Hu1, Jixiang Xing2, Wuritu Yang3
1State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, Institutes of Biomedical Sciences, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China; Inner Mongolia Key Laboratory of Life Health and Bioinformatics, School of Life Science and Technology, Inner Mongolia University of Science and Technology, Baotou 014010, China.
None:
Alternative splicing (AS) in single cell is crucial for cell heterogeneity, gene expression and transcriptome diversity. However, given the complexity of AS analysis in single-cell RNA sequencing (scRNA-seq), employing a continuous and iterative process to refine data and uncover relevant latent information is crucial. While several tools have been developed to address various aspects of scRNA-seq AS analysis, a versatile and user-friendly web application that can perform all essential steps of AS analysis on scRNA-seq data is still lacking. Here, we made significant advancements in improving the usability and functionality of MARVEL. Firstly, we developed a Python package that can easily and efficiently generate input files, reducing the technical barrier. Secondly, we developed a Shiny-based R package that extends MARVEL's analysis capabilities to multiple cell populations, enabling interactive, code-free ex-ploration of AS and gene expression dynamics at single-cell level. The package, named ScASplicer (Single-Cell Alternative Splicing Shiny Explorer), provides a user-friendly platform for more efficient and comprehensive single-cell AS analysis.
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