Streamlined analysis of duplex sequencing data with Du Novo

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

Research output: Contribution to journalArticle

10 Scopus citations

Abstract

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 http://usegalaxy.org/duplex.

Original languageEnglish (US)
Article number180
JournalGenome biology
Volume17
Issue number1
DOIs
StatePublished - Aug 26 2016

All Science Journal Classification (ASJC) codes

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

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