The advent of single-molecule third generation sequencing technologies provide new possibilities for the detection of fusion transcripts in sequencing data. Here, we test three long-read fusions detection tools on simulated data, compare various tooling parameters and compare the performance between long-read and short-read fusion detection tools. We also use our fusion transcript detection pipeline to describe fusions transcripts detected in U87 and U937 glioblastoma cell lines. We find that

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... ngGF is the most capable of the long-read fusion detect tools at identifying the most simulated fusion transcripts. While the short read fusion transcript detection tool, Arriba, had similar recall to some of the long-read tools, its precision was found to be much lower. Several fusions with ample evidence were found in u87 and u937 cell lines.