Research
Print page Print page
Switch language
The Capital Region of Denmark - a part of Copenhagen University Hospital
Published

SvABA: genome-wide detection of structural variants and indels by local assembly

Research output: Contribution to journalJournal articleResearchpeer-review

DOI

  1. The identification and functional annotation of RNA structures conserved in vertebrates

    Research output: Contribution to journalJournal articleResearchpeer-review

  1. Molecular Evolution of Early-Onset Prostate Cancer Identifies Molecular Risk Markers and Clinical Trajectories

    Research output: Contribution to journalJournal articleResearchpeer-review

  2. The landscape of genomic alterations across childhood cancers

    Research output: Contribution to journalJournal articleResearchpeer-review

  3. Mitochondrial mutations drive prostate cancer aggression

    Research output: Contribution to journalJournal articleResearchpeer-review

  4. Genomes of early onset prostate cancer

    Research output: Contribution to journalJournal articleResearchpeer-review

  • Jeremiah A Wala
  • Pratiti Bandopadhayay
  • Noah Greenwald
  • Ryan O'Rourke
  • Ted Sharpe
  • Chip Stewart
  • Steve Schumacher
  • Yilong Li
  • Joachim Weischenfeldt
  • Xiaotong Yao
  • Chad Nusbaum
  • Peter Campbell
  • Gad Getz
  • Matthew Meyerson
  • Cheng-Zhong Zhang
  • Marcin Imielinski
  • Rameen Beroukhim
View graph of relations

Structural variants (SVs), including small insertion and deletion variants (indels), are challenging to detect through standard alignment-based variant calling methods. Sequence assembly offers a powerful approach to identifying SVs, but is difficult to apply at scale genome-wide for SV detection due to its computational complexity and the difficulty of extracting SVs from assembly contigs. We describe SvABA, an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide local assembly with low memory and computing requirements. We evaluated SvABA's performance on the NA12878 human genome and in simulated and real cancer genomes. SvABA demonstrates superior sensitivity and specificity across a large spectrum of SVs and substantially improves detection performance for variants in the 20-300 bp range, compared with existing methods. SvABA also identifies complex somatic rearrangements with chains of short (<1000 bp) templated-sequence insertions copied from distant genomic regions. We applied SvABA to 344 cancer genomes from 11 cancer types and found that short templated-sequence insertions occur in ∼4% of all somatic rearrangements. Finally, we demonstrate that SvABA can identify sites of viral integration and cancer driver alterations containing medium-sized (50-300 bp) SVs.

Original languageEnglish
JournalGenome Research
Volume28
Issue number4
Pages (from-to)581-591
ISSN1088-9051
DOIs
Publication statusPublished - 13 Mar 2018

    Research areas

  • Journal Article

ID: 53452796