recipe bioconductor-m3drop

Michaelis-Menten Modelling of Dropouts in single-cell RNASeq



GPL (>=2)




biotools: m3drop, doi: 10.1002/1873-3468.12684

This package fits a Michaelis-Menten model to the pattern of dropouts in single-cell RNASeq data. This model is used as a null to identify significantly variable (i.e. differentially expressed) genes for use in downstream analysis, such as clustering cells.

package bioconductor-m3drop

(downloads) docker_bioconductor-m3drop



depends r-base:


depends r-bbmle:

depends r-gplots:

depends r-hmisc:

depends r-irlba:

depends r-matrix:

depends r-matrixstats:

depends r-numderiv:

depends r-rcolorbrewer:

depends r-reldist:

depends r-statmod:



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-m3drop

and update with::

   mamba update bioconductor-m3drop

To create a new environment, run:

mamba create --name myenvname bioconductor-m3drop

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-m3drop/tags`_ for valid values for ``<tag>``)

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