Structural variant breakpoint detection with novoBreak

Academic Article

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.
  • Authors

    Published In

    Digital Object Identifier (doi)

    Author List

  • Chong Z; Chen K
  • Start Page

  • 129
  • End Page

  • 141
  • Volume

  • 1833