Threshold determination in droplet digital PCR experiments using extreme value theory

Droplet digital polymerase chain reaction (ddPCR) is a recently developed method for nucleic acid quantification that allows for more accurate and precise estimation of nucleic acid concentrations. By splitting up a sample into about 14000 droplets using microfluidic technology and subsequently counting the numbers of negative (no nucleic acid was initially present) and positive (nucleic acid was initially present) droplets, the concentration of the nucleic acid can be determined. Each droplet is classified as positive or negative depending on its fluorescence intensity. Thus, setting a correct fluorescence level threshold is needed to accurately identify the presence or absence of target nucleic acid. We demonstrate some drawbacks of currently available methods and show how extreme value theory (EVT) can be used to model the maximum fluorescence intensity of the negative droplets using negative control samples (no target nucleic acid present). We show how we subsequently select a final threshold. We discuss some important considerations when applying EVT and how this translates to the ddPCR case.