recipe bioconductor-scmeth

Functions to conduct quality control analysis in methylation data






Functions to analyze methylation data can be found here. Some functions are relevant for single cell methylation data but most other functions can be used for any methylation data. Highlight of this workflow is the comprehensive quality control report.

package bioconductor-scmeth

(downloads) docker_bioconductor-scmeth



depends bioconductor-annotationhub:


depends bioconductor-annotatr:


depends bioconductor-biostrings:


depends bioconductor-bsgenome:


depends bioconductor-bsseq:


depends bioconductor-delayedarray:


depends bioconductor-genomeinfodb:


depends bioconductor-genomicranges:


depends bioconductor-hdf5array:


depends bioconductor-summarizedexperiment:


depends r-base:


depends r-dt:

depends r-knitr:

depends r-reshape2:

depends r-rmarkdown:



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-scmeth

and update with::

   mamba update bioconductor-scmeth

To create a new environment, run:

mamba create --name myenvname bioconductor-scmeth

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

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