ggsashimi

ggsashimi visualizes alternative splicing by generating sashimi plots from RNA-seq data to compare splice junction read support across multiple samples within specified genomic regions.

Key Features:

• Multi-sample visualization: Generates individual and aggregated sashimi plots for single RNA-seq experiments and groups of experiments to compare splicing patterns across samples.
• Support for large genomic regions: Scales down the segments between splice sites to represent large genomic regions while preserving splice-site detail.
• Annotation-independent: Operates without requiring external gene annotations.
• Compatibility with bioinformatics formats: Supports widely used bioinformatics file formats for integration into analysis workflows.
• Implementation: Implemented in Python and internally generates R code for plotting.

Scientific Applications:

• Alternative splicing analysis: Visualizes and compares alternative splicing events and splice junction usage across samples.
• Gene expression and regulation studies: Supports investigation of splicing contributions to gene expression regulation using RNA-seq junction read data.
• Disease research (including cancer): Compares splicing alterations between conditions in disease-focused studies, including cancer research.
• Developmental and comparative studies: Enables multi-sample splicing comparisons relevant to developmental biology and other comparative analyses.

Methodology:

Given a specified genomic region, ggsashimi processes RNA-seq data to compute and plot reads spanning splice junctions as sashimi plots and can aggregate read counts from multiple experiments into combined plots for comparison across samples or conditions.