recipe bioconductor-cyanofilter

Phytoplankton Population Identification using Cell Pigmentation and/or Complexity






An approach to filter out and/or identify phytoplankton cells from all particles measured via flow cytometry pigment and cell complexity information. It does this using a sequence of one-dimensional gates on pre-defined channels measuring certain pigmentation and complexity. The package is especially tuned for cyanobacteria, but will work fine for phytoplankton communities where there is at least one cell characteristic that differentiates every phytoplankton in the community.

package bioconductor-cyanofilter

(downloads) docker_bioconductor-cyanofilter



depends bioconductor-biobase:


depends bioconductor-flowclust:


depends bioconductor-flowcore:


depends bioconductor-flowdensity:


depends r-base:


depends r-cytometree:

depends r-ggally:

depends r-ggplot2:

depends r-mrfdepth:



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-cyanofilter

and update with::

   mamba update bioconductor-cyanofilter

To create a new environment, run:

mamba create --name myenvname bioconductor-cyanofilter

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-cyanofilter/tags`_ for valid values for ``<tag>``)

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