Digital PCR cluster predictor: a universal R-package and shiny app for the automated analysis of multiplex digital PCR data

Alfonso De Falco*, Christophe M. Olinger, Barbara Klink, Michel Mittelbronn, Daniel Stieber

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)

Abstract

Digital polymerase chain reaction (dPCR) is an emerging technology that enables accurate and sensitive quantification of nucleic acids. Most available dPCR systems have two channel optics, with ad hoc software limited to the analysis of single and duplex assays. Although multiplexing strategies were developed, variable assay designs, dPCR systems, and the analysis of low DNA input data restricted the ability for a universal automated clustering approach. To overcome these issues, we developed dPCR Cluster Predictor (dPCP), an R package and a Shiny app for automated analysis of up to 4-plex dPCR data. dPCP can analyse and visualize data generated by multiple dPCR systems carrying out accurate and fast clustering not influenced by the amount and integrity of input of nucleic acids. With the companion Shiny app, the functionalities of dPCP can be accessed through a web browser.

Original languageEnglish
JournalBioinformatics
Volume39
Issue number5
Early online date22 Apr 2023
DOIs
Publication statusPublished - 4 May 2023

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