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    twoddpcr: An R/Bioconductor package and Shiny app for Droplet Digital PCR analysis.

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    Authors
    Chiu, Anthony
    Ayub, Mahmood
    Dive, Caroline
    Brady, Ged
    Miller, Crispin J
    Affiliation
    Clinical and Experimental Pharmacology Group, Cancer Research UK Manchester Institute, Manchester, M20 4BX
    Issue Date
    2017-05-05
    
    Metadata
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    Abstract
    Droplet Digital PCR (ddPCR) is a sensitive platform used to quantify specific nucleic acid molecules amplified by polymerase chain reactions. Its sensitivity makes it particularly useful for the detection of rare mutant molecules, such as those present in a sample of circulating free tumour DNA obtained from cancer patients. ddPCR works by partitioning a sample into individual droplets for which the majority contain only zero or one target molecule. Each droplet then becomes a reaction chamber for PCR, which through the use of fluorochrome labelled probes allows the target molecules to be detected by measuring the fluorescence intensity of each droplet. The technology supports two channels, allowing, for example, mutant and wild type molecules to be detected simultaneously in the same sample. As yet, no open source software is available for the automatic gating of two channel ddPCR experiments in the case where the droplets can be grouped into four clusters. Here, we present an open source R package 'twoddpcr', which uses Poisson statistics to estimate the number of molecules in such two channel ddPCR data. Using the Shiny framework, an accompanying graphical user interface (GUI) is also included for the package, allowing users to adjust parameters and see the results in real-time.
    Citation
    twoddpcr: An R/Bioconductor package and Shiny app for Droplet Digital PCR analysis. 2017 Bioinformatics
    Journal
    Bioinformatics
    URI
    http://hdl.handle.net/10541/620420
    DOI
    10.1093/bioinformatics/btx308
    PubMed ID
    28475662
    Type
    Article
    Language
    en
    ISSN
    1367-4811
    ae974a485f413a2113503eed53cd6c53
    10.1093/bioinformatics/btx308
    Scopus Count
    Collections
    All Paterson Institute for Cancer Research

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