Streamlined analysis of duplex sequencing data with Du Novo

Nicholas Stoler, Barbara Arbeithuber, Wilfried Guiblet, Kateryna D. Makova, Anton Nekrutenko

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


Duplex sequencing was originally developed to detect rare nucleotide polymorphisms normally obscured by the noise of high-throughput sequencing. Here we describe a new, streamlined, reference-free approach for the analysis of duplex sequencing data. We show the approach performs well on simulated data and precisely reproduces previously published results and apply it to a newly produced dataset, enabling us to type low-frequency variants in human mitochondrial DNA. Finally, we provide all necessary tools as stand-alone components as well as integrate them into the Galaxy platform. All analyses performed in this manuscript can be repeated exactly as described at

Original languageEnglish (US)
Article number180
JournalGenome biology
Issue number1
StatePublished - Aug 26 2016

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Cell Biology


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