ASpli2

ASpli2 performs genome-wide analysis of alternative splicing from Next Generation Sequencing (NGS) data in R by quantifying differential usage of subgenic features and junction-based local splicing changes to identify annotated and novel events across complex experimental designs.

Key Features:

• Implementation: Implemented in R for computational analysis of splicing signals.
• Genome-wide analysis: Performs genome-wide detection and quantification of alternative splicing events from NGS data.
• Dual analytical approaches: Integrates differential usage analysis of subgenic features with junction-based descriptions of local splicing changes.
• Annotated and novel event detection: Detects both annotated and non-annotated (novel) alternative splicing events using combined signals.
• Bin-associated signals: Utilizes bin-associated signals to improve recall while maintaining competitive precision.
• Signal consolidation: Consolidates feature-usage and junction signals into a unified framework for identifying splicing alterations.
• Validation: Validated using analyses of simulated and real datasets.
• Complex experimental designs: Supports detection of splicing changes across complex experimental designs.

Scientific Applications:

• Differential splicing detection: Identification of differential alternative splicing events across conditions and experimental designs.
• Novel junction discovery: Detection of novel splice junctions and local splicing changes not present in annotations.
• Splicing repertoire characterization: Exploration of the complexity of the general splicing repertoire across diverse experimental conditions.
• Method benchmarking: Validation and benchmarking of splicing-detection approaches using simulated and real NGS datasets.

Methodology:

Combines differential usage analysis of subgenic features with junction-based descriptions of local splicing changes, consolidates bin-associated and junction signals for event detection, and has been validated on simulated and real datasets.