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 language | English (US) |
---|---|
Article number | 180 |
Journal | Genome biology |
Volume | 17 |
Issue number | 1 |
DOIs | |
State | Published - Aug 26 2016 |
All Science Journal Classification (ASJC) codes
- Ecology, Evolution, Behavior and Systematics
- Genetics
- Cell Biology