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Structural Variant Breakpoint Detection with novoBreak

  • Zechen ChongEmail author
  • Ken ChenEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1833)

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.

Key words

Structural variations Algorithm Next generation sequencing data analysis DNA sequence analysis Genomic rearrangement De novo assembly k-mer Genetic variation 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Genetics and Informatics Institute, School of MedicineThe University of Alabama at BirminghamBirminghamUSA
  2. 2.Department of Bioinformatics and Computational BiologyThe University of Texas MD Anderson Cancer CenterHoustonUSA

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