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Digital PCR-based Competitive Index for High-throughput Analysis of Fitness in Salmonella
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Digital PCR cluster predictor: a universal R-package and shiny app for the automated analysis of multiplex digital
Alfonso De Falco1,2,3, Christophe M Olinger1, Barbara Klink1,4
1National Center of Genetics (NCG), Laboratoire National de Santé (LNS), Dudelange 3555, Luxembourg.
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.
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