twoddpcr

Classify 2-d Droplet Digital PCR (ddPCR) data and quantify the number of starting molecules


Bioconductor version: Release (3.19)

The twoddpcr package takes Droplet Digital PCR (ddPCR) droplet amplitude data from Bio-Rad's QuantaSoft and can classify the droplets. A summary of the positive/negative droplet counts can be generated, which can then be used to estimate the number of molecules using the Poisson distribution. This is the first open source package that facilitates the automatic classification of general two channel ddPCR data. Previous work includes 'definetherain' (Jones et al., 2014) and 'ddpcRquant' (Trypsteen et al., 2015) which both handle one channel ddPCR experiments only. The 'ddpcr' package available on CRAN (Attali et al., 2016) supports automatic gating of a specific class of two channel ddPCR experiments only.

Author: Anthony Chiu [aut, cre]

Maintainer: Anthony Chiu <anthony at achiu.me>

Citation (from within R, enter citation("twoddpcr")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("twoddpcr")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("twoddpcr")
twoddpcr: A package for Droplet Digital PCR analysis HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews Classification, Software, ddPCR
Version 1.28.0
In Bioconductor since BioC 3.5 (R-3.4) (7.5 years)
License GPL-3
Depends R (>= 3.4)
Imports class, ggplot2, hexbin, methods, scales, shiny, stats, utils, RColorBrewer, S4Vectors
System Requirements
URL http://github.com/CRUKMI-ComputationalBiology/twoddpcr/
Bug Reports http://github.com/CRUKMI-ComputationalBiology/twoddpcr/issues/
See More
Suggests devtools, knitr, reshape2, rmarkdown, testthat, BiocStyle
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package twoddpcr_1.28.0.tar.gz
Windows Binary (x86_64) twoddpcr_1.28.0.zip
macOS Binary (x86_64) twoddpcr_1.28.0.tgz
macOS Binary (arm64) twoddpcr_1.28.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/twoddpcr
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/twoddpcr
Bioc Package Browser https://code.bioconductor.org/browse/twoddpcr/
Package Short Url https://bioconductor.org/packages/twoddpcr/
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