Low copy target detection by Droplet Digital PCR through application of a novel open access bioinformatic pipeline, 'definetherain'

Mathew Jones, James Williams, Kathleen Gärtner, Rodney Phillips, Jacob Hurst, John Frater*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

131 Citations (Scopus)

Abstract

Droplet Digital PCR (ddPCR) represents a new and alternative platform to conventional quantitative-PCR (qPCR) for the quantitation of DNA templates. However, the proposed improvement in sensitivity and reproducibility offered by ddPCR is not yet fully proven, partly because the delineation between positive and negative responses is not always clear.Data are presented demonstrating the sensitivity of the ddPCR system to both reagent concentrations and choice of cut-off for defining positive and negative results. By implementing k-nearest clustering, cut-offs are produced that improve the accuracy of ddPCR where target DNA is present at low copy numbers, a key application of ddPCR. This approach is applied to human albumin and HIV-1 proviral DNA ddPCR quantitative protocols. This tool is coded in JavaScript and has been made available for free in a web browser at http://www.definetherain.org.uk. Optimisation of the analyses of raw ddPCR data using 'definetherain' indicates that low target number detection can be improved by its implementation. Further application to patient samples will help define the clinical utility of this approach.

Original languageEnglish
Pages (from-to)46-53
Number of pages8
JournalJournal of Virological Methods
Volume202
DOIs
Publication statusPublished - 15 Jun 2014
Externally publishedYes

Keywords

  • Droplet Digital PCR
  • HIV-1
  • K means clustering
  • Quantitative PCR

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