Paired-end transcriptome sequencing has emerged as the primary assay to detect expressed gene fusions. Sensitivity, specificity, and algorithm run times are key factors for a fusion detection algorithm. The basic fusion discovery approach begins with first identifying paired-end reads with each end mapping to two different genes. Next, de novo assembly of reads partially aligning to the two genes identifies the putative fusion junction. Finally, a series of filters are applied to remove false positives. We implemented these steps in an algorithm called Minimum Overlap Junction Optimizer (MOJO). Using a combination of cancer cell lines and primary tumors we show that MOJO has the highest sensitivity and specificity compared to six other published methods. MOJO is ~5x faster than the next best performing method.

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