recipe bioconductor-milor

Differential neighbourhood abundance testing on a graph



GPL-3 + file LICENSE



Milo performs single-cell differential abundance testing. Cell states are modelled as representative neighbourhoods on a nearest neighbour graph. Hypothesis testing is performed using a negative bionomial generalized linear model.

package bioconductor-milor

(downloads) docker_bioconductor-milor



depends bioconductor-biocgenerics:


depends bioconductor-biocneighbors:


depends bioconductor-biocparallel:


depends bioconductor-biocsingular:


depends bioconductor-edger:


depends bioconductor-limma:


depends bioconductor-s4vectors:


depends bioconductor-singlecellexperiment:


depends bioconductor-summarizedexperiment:


depends r-base:


depends r-cowplot:

depends r-dplyr:

depends r-ggbeeswarm:

depends r-ggplot2:

depends r-ggraph:

depends r-ggrepel:

depends r-gtools:

depends r-igraph:

depends r-irlba:

depends r-matrix:


depends r-matrixstats:

depends r-patchwork:

depends r-rcolorbrewer:

depends r-stringr:

depends r-tibble:

depends r-tidyr:



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-milor

and update with::

   mamba update bioconductor-milor

To create a new environment, run:

mamba create --name myenvname bioconductor-milor

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

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