Structural gene fusion rearrangements leading to aberrant signaling are frequently detected in many cancer types. Gene fusions have significant prognostic and predictive value and are screened as part of molecular pathology testing for patient management. Many bioinformatic approaches have been developed to detect fusion mutations including whole-genome sequencing, targeted-based hybridization capture, and transcriptome-based approaches. Here we describe the most commonly used experimental methods to sequence and identify gene fusions using either DNA or RNA. We contrast experimental approaches both in the research and diagnostic setting and describe typical bioinformatic pipelines and software packages used to identify fusions.