Accurate detection of genomic fusions by high-throughput sequencing in clinical samples with inadequate tumor purity and formalin-fixed paraffin embedded (FFPE) tissue is an essential task in precise oncology. We developed the fusion detection algorithm Junction Location Identifier (JuLI) for optimization of high-depth clinical sequencing. We implemented novel filtering steps to minimize false positives and a joint calling function to increase sensitivity in clinical setting. We comprehensively validated the algorithm using high-depth sequencing data from cancer cell lines and clinical samples and whole genome sequencing data from NA12878. We showed that JuLI outperformed state-of-the-art fusion callers in cases with high-depth clinical sequencing and rescued a driver fusion from false negative in plasma cell-free DNA. JuLI is freely available via GitHub (https://github.com/sgilab/JuLI). READ ARTICLE
The Journal of Molecular Diagnostics DOI:10.1016/j.jmoldx.2019.10.015
Authors: Hyun-Tae Shin, Nayoung K. D. Kim, Jae Won Yun, Boram Lee, Sungkyu Kyung, Ki-Wook Lee, Daeun Ryu, Jinho Kim, Joon Seol Bae, Donghyun Park, Yoon-La Choi, Se-Hoon Lee, Myung-Ju Ahn, Keunchil Park, Woong-Yang Park