ScASplicer: An interactive shiny/R application for alternative splicing analysis of single-cell sequencing.

Abstract

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.