recipe bioconductor-remp

Repetitive Element Methylation Prediction

Homepage:

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

License:

GPL-3

Recipe:

/bioconductor-remp/meta.yaml

Machine learning-based tools to predict DNA methylation of locus-specific repetitive elements (RE) by learning surrounding genetic and epigenetic information. These tools provide genomewide and single-base resolution of DNA methylation prediction on RE that are difficult to measure using array-based or sequencing-based platforms, which enables epigenome-wide association study (EWAS) and differentially methylated region (DMR) analysis on RE.

package bioconductor-remp

versions:

1.30.0-0,  1.26.0-0,  1.24.0-0,  1.22.0-0,  1.18.0-0,  1.16.0-0,  1.14.0-1,  1.14.0-0,  1.12.0-0, 

1.30.0-0,  1.26.0-0,  1.24.0-0,  1.22.0-0,  1.18.0-0,  1.16.0-0,  1.14.0-1,  1.14.0-0,  1.12.0-0,  1.10.0-0,  1.8.1-1

depends bioconductor-annotationhub:

>=3.14.0,<3.15.0

depends bioconductor-biocgenerics:

>=0.52.0,<0.53.0

depends bioconductor-biocparallel:

>=1.40.0,<1.41.0

depends bioconductor-biostrings:

>=2.74.0,<2.75.0

depends bioconductor-bsgenome:

>=1.74.0,<1.75.0

depends bioconductor-genomeinfodb:

>=1.42.0,<1.43.0

depends bioconductor-genomicranges:

>=1.58.0,<1.59.0

depends bioconductor-impute:

>=1.80.0,<1.81.0

depends bioconductor-iranges:

>=2.40.0,<2.41.0

depends bioconductor-minfi:

>=1.52.0,<1.53.0

depends bioconductor-org.hs.eg.db:

>=3.20.0,<3.21.0

depends bioconductor-rtracklayer:

>=1.66.0,<1.67.0

depends bioconductor-s4vectors:

>=0.44.0,<0.45.0

depends bioconductor-summarizedexperiment:

>=1.36.0,<1.37.0

depends r-base:

>=4.4,<4.5.0a0

depends r-caret:

depends r-doparallel:

depends r-foreach:

depends r-iterators:

depends r-kernlab:

depends r-ranger:

depends r-readr:

depends r-settings:

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-remp

and update with::

   mamba update bioconductor-remp

To create a new environment, run:

mamba create --name myenvname bioconductor-remp

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-remp:<tag>

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

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