Digital PCR Partition Classification
Matthijs Vynck1,2, Yao Chen1,2,3, David Gleerup1,2
1Digital PCR Consortium, Ghent University, Ghent, Belgium.
Background:
Partition classification is a critical step in the digital PCR data analysis pipeline. A range of partition classification methods have been developed, many motivated by specific experimental setups. An overview of these partition classification methods is lacking and their comparative properties are often unclear, likely impacting the proper application of these methods.
Content:
This review provides a summary of all available digital PCR partition classification approaches and the challenges they aim to overcome, serving as a guide for the digital PCR practitioner wishing to apply them. We additionally discuss strengths and weaknesses of these methods, which can further guide practitioners in vigilant application of these existing methods. This review provides method developers with ideas for improving methods or designing new ones. The latter is further stimulated by our identification and discussion of application gaps in the literature, for which there are currently no or few methods available.
Summary:
This review provides an overview of digital PCR partition classification methods, their properties, and potential applications. Ideas for further advances are presented and may bolster method development.
