bio-splicing-pipeline

To run alternative splicing analysis from raw RNA-seq data, this pipeline orchestrates STAR 2-pass alignment, junction QC, rMATS-turbo differential testing, and sashimi visualization automatically. It handles the full workflow from FASTQ files to final differential splicing results.

The best way to perform differential splicing analysis across multiple samples is using rMATS-turbo within this pipeline. It processes aligned reads to identify significant splicing events and filters results for robust differential testing across your sample groups.

STAR 2-pass alignment improves junction discovery by performing an initial alignment to identify splice junctions, then realigning reads using these discovered junctions. This approach ensures robust junction mapping and accurate gene counts for downstream splicing analysis.

Yes, you can visualize significant alternative splicing events identified by rMATS-turbo using sashimi visualizations. This pipeline generates sashimi plots to illustrate top differential splicing events for clear biological interpretation of your RNA-seq data.

Yes, this splicing pipeline supports optional isoform switching analysis using IsoformSwitchAnalyzeR. It provides deeper transcript-level insights by analyzing isoform switching events alongside the core differential splicing results from rMATS-turbo.

Junction QC is required before differential splicing analysis to assess sequencing depth and data quality. This pipeline performs junction QC checks to ensure your RNA-seq data meets quality thresholds, preventing unreliable results from low-quality alignments in rMATS-turbo.