recipe bioconductor-melissa

Bayesian clustering and imputationa of single cell methylomes



GPL-3 | file LICENSE



Melissa is a Baysian probabilistic model for jointly clustering and imputing single cell methylomes. This is done by taking into account local correlations via a Generalised Linear Model approach and global similarities using a mixture modelling approach.

package bioconductor-melissa

(downloads) docker_bioconductor-melissa



depends bioconductor-biocstyle:


depends bioconductor-bprmeth:


depends bioconductor-genomicranges:


depends r-assertthat:

depends r-base:


depends r-cowplot:

depends r-data.table:

depends r-doparallel:

depends r-foreach:

depends r-ggplot2:

depends r-magrittr:

depends r-matrixcalc:

depends r-mclust:

depends r-mcmcpack:

depends r-mvtnorm:

depends r-rocr:

depends r-truncnorm:



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-melissa

and update with::

   mamba update bioconductor-melissa

To create a new environment, run:

mamba create --name myenvname bioconductor-melissa

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

Download stats