Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.13.250167v1?rss=1 Authors: Halperin, R. F., Hedge, A., Lang, J. D., Raupach, E. A., C4RCD Research Group,, Legendre, C., Liang, W. S., LoRusso, P., Sekulic, A., Sosman, J. A., Trent, J. M., Rangasamy, S., Pirrotte, P., Schork, N. J. Abstract: Here we present a novel statistical approach to splicing outlier and differential splicing detection, implemented in a software package called Bisbee. We leverage Bisbee's prediction of protein level effects to benchmark using matched RNAseq and mass spectrometry data from normal tissues. Bisbee exhibits improved sensitivity and specificity over existing approaches. We applied Bisbee to confirm a pathogenic splicing event in a rare disease and to identify tumor-specific splice isoforms associated with an oncogenic splice factor mutation. We also identified common tumor associated splice isoforms replicated in an independent dataset, demonstrating the utility of Bisbee in discovering disease relevant splice variants. Copy rights belong to original authors. Visit the link for more info