Journal article
SONiCS : PCR stutter noise correction in genome-scale microsatellites
Bioinformatics
2018
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Source: InCites
Abstract
<p>Motivation: Massively parallel capture of short tandem repeats (STRs, or microsatellites) provides a strategy for population genomic and demographic analyses at high resolution with or without a reference genome. However, the high Polymerase Chain Reaction (PCR) cycle numbers needed for target capture experiments create genotyping noise through polymerase slippage known as PCR stutter.<br />Results: We developed SONiCS-Stutter mONte Carlo Simulation-a solution for stutter correction based on dense forward simulations of PCR and capture experimental conditions. To test SONiCS, we genotyped a 2499-marker STR panel in 22 humpback dolphins (Sousa sahulensis) using target capture, and generated capillary-based genotypes to validate 5 of these markers. In these 110 comparisons, SONiCS showed a 99.1% accuracy rate and a 98.2% genotyping success rate, miscalling a single allele in a marker with low sequence coverage and rejecting another as un-callable.<br />Availability: Source code and documentation for SONiCS is freely available at https://github.com/kzkedzierska/sonics. Raw read data used in experimental validation of SONiCS have been deposited in the Sequence Read Archive under accession number SRP135756.<br />Supplementary information: Supplementary data are available at Bioinformatics online.</p>
Details
- Title
- SONiCS : PCR stutter noise correction in genome-scale microsatellites
- Creators
- Katarzyna Z Kedzierska - University of Virginia, USALivia Gerber - University of Zurich, SwitzerlandDaniele DB Cagnazzi - Southern Cross UniversityMichael Krützen - University of Zurich, SwitzerlandAakrosh Ratan - University of Virginia, USALogan Kistler - Smithsonian Institution, USA
- Publication Details
- Bioinformatics
- Identifiers
- 4559; 991012820855502368
- Academic Unit
- Marine Ecology Research Centre; Faculty of Science and Engineering; Science; School of Environment, Science and Engineering
- Resource Type
- Journal article