recipe bioconductor-compartmap

Higher-order chromatin domain inference in single cells from scRNA-seq and scATAC-seq



GPL-3 + file LICENSE



Compartmap performs direct inference of higher-order chromatin from scRNA-seq and scATAC-seq. This package implements a James-Stein estimator for computing single-cell level higher-order chromatin domains. Further, we utilize random matrix theory as a method to de-noise correlation matrices to achieve a similar "plaid-like" patterning as observed in Hi-C and scHi-C data.

package bioconductor-compartmap

(downloads) docker_bioconductor-compartmap



depends bioconductor-biocsingular:


depends bioconductor-delayedarray:


depends bioconductor-delayedmatrixstats:


depends bioconductor-genomicranges:


depends bioconductor-hdf5array:


depends bioconductor-raggedexperiment:


depends bioconductor-rtracklayer:


depends bioconductor-summarizedexperiment:


depends r-base:


depends r-ggplot2:

depends r-matrix:

depends r-reshape2:

depends r-rmtstat:

depends r-scales:



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-compartmap

and update with::

   mamba update bioconductor-compartmap

To create a new environment, run:

mamba create --name myenvname bioconductor-compartmap

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

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