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Genome Biol. 2016 Aug 26;17(1):180. doi: 10.1186/s13059-016-1039-4.

Streamlined analysis of duplex sequencing data with Du Novo.

Author information

1
Graduate Program in Bioinformatics and Genomics, The Huck Institutes for the Life Sciences, Penn State University, 505 Wartik Lab, University Park, PA, 16802, USA.
2
Institute of Biophysics, Johannes Kepler University, Linz, Austria.
3
Department of Biology, Penn State University, 310 Wartik Lab, University Park, PA, 16802, USA. kdm16@psu.edu.
4
Graduate Program in Bioinformatics and Genomics, The Huck Institutes for the Life Sciences, Penn State University, 505 Wartik Lab, University Park, PA, 16802, USA. aun1@psu.edu.
5
Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA. aun1@psu.edu.

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 .

KEYWORDS:

Duplex sequencing; Genomic data analysis; Low frequency polymorphism discovery; Next generation sequencing

PMID:
27566673
PMCID:
PMC5000403
DOI:
10.1186/s13059-016-1039-4
[Indexed for MEDLINE]
Free PMC Article

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