Swan: a library for the analysis and visualization of long-read transcriptomes.

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Long-read RNA sequencing (e.g., PacBio, Oxford Nanopore) has revealed a vast number of novel transcript isoforms.
• Current visualization tools struggle to effectively analyze these complex transcript models.

Purpose of the Study:

• Introduce the Swan Python library for analyzing and visualizing transcript models derived from long-read RNA sequencing data.
• Provide a tool to overcome the limitations of existing methods in handling the complexity of new transcript isoforms.

Main Methods:

• Development of the Swan Python library (Python 3).
• Application of Swan for differential transcript expression analysis.
• Utilizing Swan to identify novel splicing events like exon skipping and intron retention.

Main Results:

• Swan identified 4909 differentially expressed transcripts between HepG2 and HFFc6 cell lines.
• Discovered 279 transcripts with differential expression independent of their parent gene.
• Found 285 reproducible exon skipping and 47 intron retention events not present in GENCODE v29 annotation.

Conclusions:

• The Swan library offers a powerful solution for analyzing and visualizing complex transcriptomic data from long-read sequencing.
• Swan facilitates the discovery of novel biological insights, including gene-independent differential expression and unannotated splicing events.
• The library is readily available for the scientific community to advance transcriptomic research.