satuRn

satuRn performs differential transcript usage (DTU) analysis to detect alternative splicing events from bulk RNA-seq and single-cell RNA sequencing (scRNA-seq) data.

Key Features:

• Performance and Scalability: Handles large-scale datasets and matches the performance of leading bulk RNA-seq DTU methods while offering enhanced scalability for scRNA-seq data.
• Quasi-Binomial Generalized Linear Modelling Framework: Employs a quasi-binomial generalized linear modelling approach that provides robust statistical analysis and control over false discovery rates (FDR).
• Flexibility in Experimental Design: Accommodates complex experimental designs and the inclusion of biological covariates for comparative analyses.
• Support for Bulk and Single-Cell Data: Applicable to both bulk RNA-seq and single-cell RNA sequencing (scRNA-seq) contexts for differential transcript usage studies.

Scientific Applications:

• Alternative Splicing Research: Identification and characterization of differential transcript usage to study alternative splicing mechanisms.
• Cancer and Disease Studies: Investigation of dysregulated splicing events implicated in diseases such as cancer.
• Large-Scale Single-Cell Transcriptomics: Analysis of high-throughput scRNA-seq datasets where scalability is required for DTU detection.

Methodology:

satuRn uses a quasi-binomial generalized linear modelling framework for DTU analysis, enabling integration of complex experimental designs and providing statistical inference with controlled false discovery rates.