Computational Comparison of Differential Splicing Tools for Targeted RNA Long-Amplicon Sequencing (rLAS)

Area of Science:

• Molecular Biology
• Bioinformatics
• Genomics

Background:

• RNA sequencing (RNA-Seq) is crucial for transcript quantification and alternative splicing analysis.
• Targeted RNA long-amplicon sequencing (rLAS) enables deep analysis of specific transcripts.
• Computational tools are vital for detecting and quantifying splicing events in RNA-Seq data.

Purpose of the Study:

• To evaluate the performance of four splicing analysis tools (MAJIQ, rMATS, MISO, SplAdder) with the targeted RNA long-amplicon sequencing (rLAS) method.
• To determine the suitability of existing splicing tools for analyzing complex splicing events in rLAS data.

Main Methods:

• Utilized known splicing events, including exon-skipping, multiple-exon-skipping, alternative 5' splicing, and alternative 3' splicing.
• Tested the performance of MAJIQ, rMATS, MISO, and SplAdder on rLAS samples.
• Compared the detection rates and accuracy of each tool for different splicing event types.

Main Results:

• MAJIQ detected all tested splicing event types, with a minor limitation in detecting one exon-skipping event.
• rMATS successfully identified all exon-skipping events but failed to detect other splicing event types.
• MISO and SplAdder demonstrated no ability to detect any of the evaluated splicing events in the rLAS samples.

Conclusions:

• MAJIQ exhibits superior performance for analyzing diverse splicing events using the rLAS technique.
• rMATS is a suitable tool for analyzing exon-skipping events within rLAS data.
• Further development or adaptation of splicing analysis tools may be necessary for comprehensive rLAS data interpretation.