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

•The requirement for protocol adaptation from qPCR to ddPCR is characterised.•A potential loss of sensitivity for ddPCR at low target numbers is reported.•A new bioinformatic tool ‘definetherain’ to improve droplet calling at low input target numbers is devised and applied.•‘Definetherain’ is made a...

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Veröffentlicht in:Journal of virological methods 2014-06, Vol.202 (100), p.46-53
Hauptverfasser: Jones, Mathew, Williams, James, Gärtner, Kathleen, Phillips, Rodney, Hurst, Jacob, Frater, John
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container_end_page 53
container_issue 100
container_start_page 46
container_title Journal of virological methods
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creator Jones, Mathew
Williams, James
Gärtner, Kathleen
Phillips, Rodney
Hurst, Jacob
Frater, John
description •The requirement for protocol adaptation from qPCR to ddPCR is characterised.•A potential loss of sensitivity for ddPCR at low target numbers is reported.•A new bioinformatic tool ‘definetherain’ to improve droplet calling at low input target numbers is devised and applied.•‘Definetherain’ is made available free of charge and open access at www.definetherain.org.uk. 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.
doi_str_mv 10.1016/j.jviromet.2014.02.020
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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. 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subjects Computational Biology - methods
Droplet Digital PCR
HIV-1
HIV-1 - genetics
Humans
k means clustering
Molecular Diagnostic Techniques - methods
Polymerase Chain Reaction - methods
Quantitative PCR
Sensitivity and Specificity
Serum Albumin - genetics
title Low copy target detection by Droplet Digital PCR through application of a novel open access bioinformatic pipeline, ‘definetherain’
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