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

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.