Fusion gene discovery in single cells from high throughput long read single cell transcriptomes

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• High throughput long-read single cell RNA sequencing enables parallel fusion gene discovery.
• Current computational tools lack the robustness for accurate fusion gene detection.

Purpose of the Study:

• To develop a robust computational tool for accurate fusion gene and splicing isoform detection.
• To address the limitations of existing bioinformatics tools in single cell RNA sequencing analysis.

Main Methods:

• Development of LongFUSE, a novel computational tool.
• Utilizing XOR logic operations and stringent filtering criteria.
• Application in both simulated and real single cell RNA sequencing data.

Main Results:

• LongFUSE accurately detects cell-specific fusion genes.
• The tool identifies various splicing isoforms of fusion genes.
• LongFUSE demonstrates superior performance compared to existing tools.

Conclusions:

• LongFUSE provides a robust and accurate solution for fusion gene discovery in single cell RNA sequencing.
• The developed tool enhances the analysis of complex transcriptomic data.
• This advancement facilitates deeper understanding of gene fusion events at the single cell level.