Benchmarking digital PCR partition classification methods with empirical and simulated duplex data.

ABSTRACT: Digital PCR (dPCR) is a highly accurate technique for the quantification of target nucleic acid(s). It has shown great potential in clinical applications, like tumor liquid biopsy and validation of biomarkers. Accurate classification of partitions based on end-point fluorescence intensities is crucial to avoid biased estimators of the concentration of the target molecules. We have evaluated many clustering methods, from general-purpose methods to specific methods for dPCR and flowcytometry, on both simulated and real-life data. Clustering method performance was evaluated by simulating various scenarios. Based on our extensive comparison of clustering methods, we describe the limits of these methods, and formulate guidelines for choosing an appropriate method. In addition, we have developed

SUBMITTER: Chen Y 

PROVIDER: S-EPMC10981767 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature