Construction of a synthetic RNA-seq data set for testing of fusion detection algorithms

Gene fusions are known to play critical roles in tumor pathogenesis. However, sensitive and specific algorithms to detect gene fusions in cancer do not currently exist. Although real RNA-seq data from cell lines or tumors can be used in testing new fusion detection algorithms, it is impossible to know the true sensitivity or specificity of an algorithm without knowing the "ground truth". For this reason we designed a synthetic control data set to assess the true and false positive and negative fusions of a a new fusion detection algorithm.