Package Recipe 'bioconductor-remp'

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:

1.34.0-0, 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,

1.34.0-0, 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:

on bioconductor-annotationhub >=4.0.0,<4.1.0
on bioconductor-biocgenerics >=0.56.0,<0.57.0
on bioconductor-biocparallel >=1.44.0,<1.45.0
on bioconductor-biostrings >=2.78.0,<2.79.0
on bioconductor-bsgenome >=1.78.0,<1.79.0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-impute >=1.84.0,<1.85.0
on bioconductor-iranges >=2.44.0,<2.45.0
on bioconductor-minfi >=1.56.0,<1.57.0
on bioconductor-org.hs.eg.db >=3.22.0,<3.23.0
on bioconductor-rtracklayer >=1.70.0,<1.71.0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-seqinfo >=1.0.0,<1.1.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on r-base >=4.5,<4.6.0a0
on r-caret
on r-doparallel
on r-foreach
on r-iterators
on r-kernlab
on r-ranger
on r-readr
on r-settings

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-remp

to add into an existing workspace instead, run:

pixi add bioconductor-remp

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-remp

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-remp

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/bioconductor-remp:<tag>

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

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-remp/README.html)