recipe bioconductor-ddpcrclust

Clustering algorithm for ddPCR data






The ddPCRclust algorithm can automatically quantify the CPDs of non-orthogonal ddPCR reactions with up to four targets. In order to determine the correct droplet count for each target, it is crucial to both identify all clusters and label them correctly based on their position. For more information on what data can be analyzed and how a template needs to be formatted, please check the vignette.

package bioconductor-ddpcrclust

(downloads) docker_bioconductor-ddpcrclust



depends bioconductor-flowcore:


depends bioconductor-flowdensity:


depends bioconductor-flowpeaks:


depends bioconductor-samspectral:


depends r-base:


depends r-clue:

depends r-ggplot2:

depends r-openxlsx:

depends r-plotrix:

depends r-r.utils:



You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-ddpcrclust

and update with::

   mamba update bioconductor-ddpcrclust

To create a new environment, run:

mamba create --name myenvname bioconductor-ddpcrclust

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `bioconductor-ddpcrclust/tags`_ for valid values for ``<tag>``)

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