recipe bioconductor-missmethyl

Analysing Illumina HumanMethylation BeadChip Data







biotools: missmethyl

Normalisation, testing for differential variability and differential methylation and gene set testing for data from Illumina's Infinium HumanMethylation arrays. The normalisation procedure is subset-quantile within-array normalisation (SWAN), which allows Infinium I and II type probes on a single array to be normalised together. The test for differential variability is based on an empirical Bayes version of Levene's test. Differential methylation testing is performed using RUV, which can adjust for systematic errors of unknown origin in high-dimensional data by using negative control probes. Gene ontology analysis is performed by taking into account the number of probes per gene on the array, as well as taking into account multi-gene associated probes.

package bioconductor-missmethyl

(downloads) docker_bioconductor-missmethyl



depends bioconductor-annotationdbi:


depends bioconductor-biobase:


depends bioconductor-biocgenerics:


depends bioconductor-genomicranges:


depends bioconductor-go.db:


depends bioconductor-illuminahumanmethylation450kanno.ilmn12.hg19:


depends bioconductor-illuminahumanmethylation450kmanifest:


depends bioconductor-illuminahumanmethylationepicanno.ilm10b4.hg19:


depends bioconductor-illuminahumanmethylationepicmanifest:


depends bioconductor-iranges:


depends bioconductor-limma:


depends bioconductor-methylumi:


depends bioconductor-minfi:




depends bioconductor-s4vectors:


depends bioconductor-summarizedexperiment:


depends r-base:


depends r-biasedurn:

depends r-ruv:

depends r-statmod:

depends r-stringr:



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-missmethyl

and update with::

   mamba update bioconductor-missmethyl

To create a new environment, run:

mamba create --name myenvname bioconductor-missmethyl

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

Download stats