MARVEL

MARVEL performs integrated alternative splicing analysis of single-cell RNA sequencing (scRNA-seq) data in R, enabling joint identification of splicing events and correlation with gene expression from plate- and droplet-based protocols.

Key Features:

• Integrated Splicing Analysis: Integrates alternative splicing event detection with single-cell gene expression profiling to analyze splicing and expression jointly.
• Applicability Across Methods: Processes scRNA-seq data generated by both plate-based and droplet-based protocols.
• Extensive Benchmarking: Validated through benchmarking against existing tools to assess performance in single-cell splicing analysis.
• Utility Demonstrated Across Datasets: Applied to multiple publicly available scRNA-seq datasets spanning diverse cell types and disease-relevant contexts.

Scientific Applications:

• Splicing landscape characterization: Characterizes alternative splicing landscapes at single-cell resolution.
• Cellular heterogeneity analysis: Detects cell-to-cell heterogeneity arising from alternative splicing and relates it to gene expression patterns.
• Disease-related splicing investigation: Investigates splicing changes across disease-relevant cell types and datasets.

Methodology:

Integrates splicing and gene expression data at the single-cell level to identify splicing events and correlate them with gene expression patterns, and includes benchmarking against other tools and application to public scRNA-seq datasets.