JuLI: accurate detection of DNA fusions in clinical sequencing for precision oncology

Shin, H.-T.; Kim, N. K. D.; Yun, J. W.; Lee, B.; Kyung, S.; Lee, K.-W.; Ryu, D.; Kim, J.; Bae, J. S.; Park, D.; Choi, Y.-L.; Lee, S.-H.; Ahn, M.-J.; Park, K.; Park, W.-Y.

doi:10.1101/521039

bioRxiv · 10.1101/521039

JuLI: accurate detection of DNA fusions in clinical sequencing for precision oncology

Shin, H.-T.·Kim, N. K. D.·Yun, J. W.·Lee, B.·Kyung, S.·Lee, K.-W.·Ryu, D.·Kim, J.·Bae, J. S.·Park, D.·Choi, Y.-L.·Lee, S.-H.·Ahn, M.-J.·Park, K.·Park, W.-Y.

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Abstract

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).

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Shin, H.-T., Kim, N. K. D., Yun, J. W., Lee, B., Kyung, S., Lee, K.-W., Ryu, D., Kim, J., Bae, J. S., Park, D., Choi, Y.-L., Lee, S.-H., Ahn, M.-J., Park, K., Park, W.-Y.. 2019-01-16. JuLI: accurate detection of DNA fusions in clinical sequencing for precision oncology. https://doi.org/10.1101/521039

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