JAFFAL

JAFFAL detects gene fusions from long-read transcriptome sequencing data, enabling characterization of full-length and multi-gene fusion transcripts for studies of cancer and structural rearrangements.

Key Features:

• Long-Read Compatibility: Tailored for third-generation sequencing platforms (Nanopore, PacBio) to leverage reads that can span entire fusion transcripts and resolve full isoform structures.
• High Accuracy and Performance: Validated on simulated data, cell line studies, and patient samples, demonstrating superior accuracy for long-read fusion detection and performance comparable to state-of-the-art short-read fusion finders.
• Transcript-Centric Approach: Builds on JAFFA principles by comparing a sample's transcriptome against a reference transcriptome to identify fusion transcripts without relying solely on genomic data.
• Single-Cell Resolution: Capable of detecting fusions at the single-cell level when applied to long-read single-cell sequencing data.
• Detection of Complex Fusions: Identifies multi-gene fusion events, including fusions spanning three genes, to characterize complex transcriptional products from structural rearrangements.

Scientific Applications:

• Cancer genomics: Identification and characterization of fusion genes relevant to tumor initiation, progression, diagnosis, prognosis, and therapeutic targeting.
• Biomarker and target discovery: Precise full-length fusion transcript characterization to aid discovery of novel diagnostic markers and potential therapeutic targets.
• Tumor heterogeneity and evolution: Analysis of single-cell long-read data to study intra-tumor heterogeneity and evolutionary trajectories mediated by fusion events.

Methodology:

Employs a transcript-centric pipeline that compares a sample's transcriptome against a reference transcriptome applied to long-read (Nanopore, PacBio) and long-read single-cell transcriptome sequencing data.