FusionAnalyser

FusionAnalyser identifies driver fusion rearrangements in human cancers from short paired-end high-throughput transcriptome sequencing data.

Key Features:

• Paired-end RNA-seq processing: Processes short paired-end sequences from high-throughput transcriptome sequencing to detect fusion transcripts.
• High specificity in detection: Demonstrated high specificity for known driver fusion events, validated using in silico generated sequencing data from 20 established human translocations and transcriptome data from chronic and acute myeloid leukemia samples.
• Novel fusion identification: Capable of discovering novel in-frame fusion events, including identification of a previously unrecognized ETS2-ERG fusion in an acute myeloid leukemia sample.
• Flexible filtering system: Provides a filtering system to tailor analyses to specific research hypotheses.
• Driver-fusion discrimination algorithms: Uses sophisticated algorithms to distinguish driver fusions with high accuracy and specificity.

Scientific Applications:

• Cancer genomics: Elucidating genetic rearrangements underlying oncogenesis across leukaemias and solid tumors using transcriptome sequencing.
• Clinical biomarker identification: Informing diagnosis, prognosis, and treatment strategy decisions by identifying clinically relevant fusion events.
• Leukaemia research: Studying molecular underpinnings of chronic and acute myeloid leukemia through detection of known and novel fusion events.

Methodology:

Processes short paired-end sequences from high-throughput transcriptome sequencing to identify fusion rearrangements using sophisticated algorithms that distinguish driver fusions, and employs a flexible filtering system to tailor analyses.