bulkrna-splicing

To detect differential splicing, this Skill processes rMATS or SUPPA2 output to identify statistically significant events based on user-defined Delta PSI and adjusted p-value cutoffs. It applies these thresholds to distinguish true differential splicing from background noise across conditions.

For differential splicing analysis, the Skill generates publication-ready plots including event type distributions, Delta PSI histograms, and splicing volcano plots. These visualizations help researchers quickly pinpoint genes with altered splicing patterns between disease and control samples.

Yes, you can use rMATS output to quantify PSI for different splicing event types. The Skill calculates Percent Spliced In values across five event categories: SE, A5SS, A3SS, MXE, and RI, providing summary statistics for each splicing pattern detected in the bulk RNA-seq data.

To identify significant alternative splicing events between conditions, apply user-defined thresholds for Delta PSI and adjusted p-value to the quantified data. The Skill automates this filtering process to pinpoint statistically significant differential splicing events for downstream biomarker discovery.

Yes, this alternative splicing analysis tool supports both rMATS and SUPPA2 output formats. It directly ingests these file types to perform PSI quantification and differential splicing detection, making it adaptable to different upstream bulk RNA-seq analysis pipelines.