recipe bioconductor-dmcfb

Differentially Methylated Cytosines via a Bayesian Functional Approach






DMCFB is a pipeline for identifying differentially methylated cytosines using a Bayesian functional regression model in bisulfite sequencing data. By using a functional regression data model, it tries to capture position-specific, group-specific and other covariates-specific methylation patterns as well as spatial correlation patterns and unknown underlying models of methylation data. It is robust and flexible with respect to the true underlying models and inclusion of any covariates, and the missing values are imputed using spatial correlation between positions and samples. A Bayesian approach is adopted for estimation and inference in the proposed method.

package bioconductor-dmcfb

(downloads) docker_bioconductor-dmcfb



depends bioconductor-biocparallel:


depends bioconductor-genomicranges:


depends bioconductor-iranges:


depends bioconductor-rtracklayer:


depends bioconductor-s4vectors:


depends bioconductor-summarizedexperiment:


depends r-arm:

depends r-base:


depends r-benchmarkme:

depends r-data.table:

depends r-fastdummies:

depends r-mass:

depends r-matrixstats:

depends r-speedglm:

depends r-tibble:



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-dmcfb

and update with::

   mamba update bioconductor-dmcfb

To create a new environment, run:

mamba create --name myenvname bioconductor-dmcfb

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

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