TopHat-Fusion

TopHat-Fusion identifies fusion transcripts from RNA sequencing (RNA-seq) data by detecting fusion junctions and novel splice variants arising from chromosomal rearrangements, enabling discovery of gene fusions relevant to disease such as cancer.

Key Features:

• RNA-seq input: Processes RNA sequencing (RNA-seq) data to interrogate the transcriptome, including coding and non-coding regions.
• Annotation-independent alignment: Aligns reads without relying on pre-existing gene annotations, enabling detection from unannotated genomic regions.
• Fusion junction detection: Aligns reads across potential fusion points to identify junctions indicative of gene fusions.
• Novel splice variant discovery: Detects novel splice variants of known genes as well as fusion transcripts originating from previously unannotated regions.
• Scalability for high-throughput data: Employs a robust algorithmic framework that handles large RNA-seq datasets typical of high-throughput sequencing.
• TopHat lineage: Extends the TopHat alignment approach to enable fusion detection.
• Known and novel fusion recovery: Recovers previously reported fusion genes and discovers novel fusions with supporting read evidence.

Scientific Applications:

• Cancer fusion discovery: Detection of gene fusions in cancer studies, with example applications in breast and prostate cancer cell lines.
• Transcriptome-wide fusion screening: Annotation-independent, transcriptome-wide identification of fusion transcripts and novel splice variants.
• Validation of reported fusions: Confirmation and validation of previously reported fusion events using RNA-seq evidence.

Methodology:

Analyzes RNA-seq reads by performing annotation-independent alignment and mapping reads across candidate fusion junctions to identify fusion transcripts within a computational framework designed for large high-throughput datasets.