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Åke Borg

Åke Borg

Principal investigator

Åke Borg

Inferring structural variant cancer cell fraction


  • Marek Cmero
  • Ke Yuan
  • Cheng Soon Ong
  • Jan Schröder
  • Niall M Corcoran
  • Tony Papenfuss
  • Christopher M Hovens
  • Florian Markowetz
  • Geoff Macintyre

Other contributions

  • Åke Borg
  • Markus Ringnér
  • Johan Staaf

Summary, in English

We present SVclone, a computational method for inferring the cancer cell fraction of structural variant (SV) breakpoints from whole-genome sequencing data. SVclone accurately determines the variant allele frequencies of both SV breakends, then simultaneously estimates the cancer cell fraction and SV copy number. We assess performance using in silico mixtures of real samples, at known proportions, created from two clonal metastases from the same patient. We find that SVclone's performance is comparable to single-nucleotide variant-based methods, despite having an order of magnitude fewer data points. As part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) consortium, which aggregated whole-genome sequencing data from 2658 cancers across 38 tumour types, we use SVclone to reveal a subset of liver, ovarian and pancreatic cancers with subclonally enriched copy-number neutral rearrangements that show decreased overall survival. SVclone enables improved characterisation of SV intra-tumour heterogeneity.


  • LUCC: Lund University Cancer Centre
  • Familial Breast Cancer
  • Breastcancer-genetics
  • Molecular Cell Biology
  • Breast/lungcancer
  • Research Group Lung Cancer

Publishing year





Nature Communications



Document type

Journal article


Nature Publishing Group


  • Medical Genetics


  • Algorithms
  • Computational Biology/methods
  • Computer Simulation
  • DNA Copy Number Variations
  • Female
  • Gene Frequency
  • Genome, Human
  • Humans
  • Liver Neoplasms/genetics
  • Male
  • Neoplasms/genetics
  • Ovarian Neoplasms/genetics
  • Pancreatic Neoplasms/genetics
  • Prostatic Neoplasms/genetics
  • Sensitivity and Specificity
  • Whole Genome Sequencing



Research group

  • Familial Breast Cancer
  • Research Group Lung Cancer


  • ISSN: 2041-1723