背景: Gene fusion events are significant sources of somatic variation across
adult and pediatric cancers and are some of the most clinically-effective
therapeutic targets, yet low consensus of RNA-Seq fusion prediction
algorithms makes therapeutic prioritization difficult. 此外, events
such as polymerase read-throughs, mis-mapping due to gene homology, 和
fusions occurring in healthy normal tissue require informed filtering,
making it difficult for researchers and clinicians to rapidly discern gene
fusions that might be true underlying oncogenic drivers of a tumor and in
some cases, appropriate targets for therapy.