Abstract
Structural variations (SVs) are an important type of genomic variants and always play a critical role for cancer development and progression. In the cancer genomics era, detecting structural variations from short sequencing data is still challenging. We developed a novel algorithm, novoBreak (Chong et al. Nat Methods 14:65-67, 2017), which achieved the highest balanced accuracy (mean of sensitivity and precision) in the ICGC-TCGA DREAM 8.5 Somatic Mutation Calling Challenge. Here we describe detailed instructions of applying novoBreak ( https://github.com/czc/nb_distribution ), an open-source software, for somatic SVs detection. We also briefly introduce how to detect germline SVs using novoBreak pipeline and how to use the Workflow ( https://cgc.sbgenomics.com/public/apps#ZCHONG/novobreak-commit/novobreak-analysis/ ) of novoBreak on the Seven Bridges Cancer Genomics Cloud.
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