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Whole genome DNA-sequencing (WGS) of paired tumor and normal samples has enabled the identification of somatic DNA changes in an unprecedented detail. Large-scale identification of somatic structural variations (SVs) for a specific cancer type will deepen our understanding of driver mechanisms in cancer progression. However, the limited number of WGS samples, insufficient read coverage, and the impurity of tumor samples that contain normal and neoplastic cells, limit reliable and accurate detection of somatic SVs.

PSSV: a novel pattern-based probabilistic approach for somatic structural variation identification