BreakFusion

BreakFusion detects gene fusions from next-generation whole transcriptome sequencing (NGS) data to identify fusion events relevant to disease mechanisms such as oncogenic processes.

Key Features:

• Hybrid Methodology: Employs a hybrid approach combining reference alignment, read-pair analysis, and de novo assembly to balance sensitivity and specificity.
• Reference Alignment: Aligns sequencing reads to a reference genome to identify known fusion breakpoints.
• Read-Pair Analysis: Analyzes paired-end reads to detect discordant or inconsistent read pairs indicative of candidate fusions.
• De Novo Assembly: Performs de novo assembly of reads to reconstruct novel fusion transcripts and discover previously uncharacterized events.
• Sensitivity and Specificity: Leverages both reference-based and de novo strategies to enhance true-positive detection while reducing false positives.
• Scalability: Supports analysis of large-scale NGS whole transcriptome datasets typical of next-generation sequencing platforms.

Scientific Applications:

• Cancer research: Detection and characterization of gene fusions to investigate oncogenic drivers and fusion-associated mechanisms.
• Diagnostic and therapeutic development: Identification of fusion events to inform targeted therapy development and the design of improved diagnostic assays.

Methodology:

Computational methods explicitly include reference alignment of sequencing reads to a reference genome, read-pair analysis of paired-end reads to detect discordant pairs, and de novo assembly to reconstruct novel fusion sequences.