recipe bioconductor-methylimp2

Missing value estimation of DNA methylation data

Homepage:

https://bioconductor.org/packages/3.20/bioc/html/methyLImp2.html

License:

GPL-3

Recipe:

/bioconductor-methylimp2/meta.yaml

This package allows to estimate missing values in DNA methylation data. methyLImp method is based on linear regression since methylation levels show a high degree of inter-sample correlation. Implementation is parallelised over chromosomes since probes on different chromosomes are usually independent. Mini-batch approach to reduce the runtime in case of large number of samples is available.

package bioconductor-methylimp2

(downloads) docker_bioconductor-methylimp2

versions:

1.2.0-0

depends bioconductor-biocparallel:

>=1.40.0,<1.41.0

depends bioconductor-champdata:

>=2.38.0,<2.39.0

depends bioconductor-summarizedexperiment:

>=1.36.0,<1.37.0

depends r-base:

>=4.4,<4.5.0a0

depends r-corpcor:

requirements:

additional platforms:

Installation

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-methylimp2

and update with::

   mamba update bioconductor-methylimp2

To create a new environment, run:

mamba create --name myenvname bioconductor-methylimp2

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 quay.io/biocontainers/bioconductor-methylimp2:<tag>

(see `bioconductor-methylimp2/tags`_ for valid values for ``<tag>``)

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