Fusion Detection Pipeline

Fusion gene detection by RNA-seq requires prior setup of several software modules and dependencies which might be troublesome. Furthermore, fusion detection tools tend to report many false positives. Therefore, we developed a detection and filtering workflow bundled into a Singularity container for a streamlined and easy-to-use application. Arriba and FusionCatcher are utilized for fusion calling. Our filtering pipeline uses read counts generated by FeatureCounts and insert size estimation by Picard Tools for calculation of our filtering metrics: Fusion Transcript Score (FTS). Further filtering is realized by a custom blacklist, our Promiscuity Score (PS) and Robustness Score (RS). Identified fusion genes are reported with evidence levels based on our filtering. This pipeline has been developed and optimized in a study of 806 AML patient samples (https://doi.org/10.3324/haematol.2021.278436).