recipe bioconductor-ramr

Detection of Rare Aberrantly Methylated Regions in Array and NGS Data

Homepage:

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

License:

Artistic-2.0

Recipe:

/bioconductor-ramr/meta.yaml

ramr is an R package for detection of low-frequency aberrant methylation events in large data sets obtained by methylation profiling using array or high-throughput bisulfite sequencing. In addition, package provides functions to visualize found aberrantly methylated regions (AMRs), to generate sets of all possible regions to be used as reference sets for enrichment analysis, and to generate biologically relevant test data sets for performance evaluation of AMR/DMR search algorithms.

package bioconductor-ramr

(downloads) docker_bioconductor-ramr

Versions:

1.18.0-11.18.0-01.14.0-01.10.0-01.8.0-01.6.0-01.2.0-01.0.0-0

Depends:
  • on bioconductor-biocgenerics >=0.56.0,<0.57.0

  • on bioconductor-biocgenerics >=0.56.0,<0.57.0a0

  • on bioconductor-genomicranges >=1.62.0,<1.63.0

  • on bioconductor-genomicranges >=1.62.1,<1.63.0a0

  • on bioconductor-iranges >=2.44.0,<2.45.0

  • on bioconductor-iranges >=2.44.0,<2.45.0a0

  • on bioconductor-s4vectors >=0.48.0,<0.49.0

  • on bioconductor-s4vectors >=0.48.0,<0.49.0a0

  • on bioconductor-seqinfo >=1.0.0,<1.1.0

  • on bioconductor-seqinfo >=1.0.0,<1.1.0a0

  • on libblas >=3.9.0,<4.0a0

  • on libcxx >=19

  • on liblapack >=3.9.0,<4.0a0

  • on liblzma >=5.8.2,<6.0a0

  • on libzlib >=1.3.1,<2.0a0

  • on r-base >=4.5,<4.6.0a0

  • on r-data.table

  • on r-rcpp

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-ramr

to add into an existing workspace instead, run:

pixi add bioconductor-ramr

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-ramr

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-ramr

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-ramr:<tag>

(see bioconductor-ramr/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.

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