Package Recipe 'bioconductor-bprmeth'

recipe bioconductor-bprmeth

Model higher-order methylation profiles

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/BPRMeth.html
License:: GPL-3 | file LICENSE
Recipe:: /bioconductor-bprmeth/meta.yaml

The BPRMeth package is a probabilistic method to quantify explicit features of methylation profiles, in a way that would make it easier to formally use such profiles in downstream modelling efforts, such as predicting gene expression levels or clustering genomic regions or cells according to their methylation profiles.

package bioconductor-bprmeth¶

Versions:

1.32.0-0, 1.28.0-0, 1.26.1-0, 1.24.0-1, 1.24.0-0, 1.20.0-2, 1.20.0-1, 1.20.0-0, 1.18.0-0,

1.32.0-0, 1.28.0-0, 1.26.1-0, 1.24.0-1, 1.24.0-0, 1.20.0-2, 1.20.0-1, 1.20.0-0, 1.18.0-0, 1.16.0-1, 1.16.0-0, 1.14.0-0, 1.12.0-0, 1.10.0-1, 1.8.1-0

Depends:

on bioconductor-biocstyle >=2.34.0,<2.35.0
on bioconductor-biocstyle >=2.34.0,<2.35.0a0
on bioconductor-genomicranges >=1.58.0,<1.59.0
on bioconductor-genomicranges >=1.58.0,<1.59.0a0
on bioconductor-iranges >=2.40.0,<2.41.0
on bioconductor-iranges >=2.40.0,<2.41.0a0
on bioconductor-s4vectors >=0.44.0,<0.45.0
on bioconductor-s4vectors >=0.44.0,<0.45.0a0
on libblas >=3.9.0,<4.0a0
on libgcc >=13
on liblapack >=3.9.0,<4.0a0
on libstdcxx >=13
on r-assertthat
on r-base >=4.4,<4.5.0a0
on r-cowplot
on r-data.table
on r-doparallel
on r-e1071
on r-earth
on r-foreach
on r-ggplot2
on r-kernlab
on r-magrittr
on r-mass
on r-matrixcalc
on r-mvtnorm
on r-randomforest
on r-rcpp >=0.12.14
on r-rcpparmadillo
on r-truncnorm

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-bprmeth

to add into an existing workspace instead, run:

pixi add bioconductor-bprmeth

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-bprmeth

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-bprmeth

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-bprmeth:<tag>

(see bioconductor-bprmeth/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-bprmeth/README.html)