recipe r-histonehmm

histoneHMM is a software to analyse ChIP-seq data of histone modifications with broad genomic footprints like H3K27me3. It allows for calling modified regions in single samples as well as for calling differentially modified regions in a comparison of two samples

Homepage:

http://histonehmm.molgen.mpg.de/

Developer docs:

https://github.com/matthiasheinig/histoneHMM

License:

GPL

Recipe:

/r-histonehmm/meta.yaml

package r-histonehmm

(downloads) docker_r-histonehmm

versions:
1.8-6,  1.8-5,  1.8-4,  1.8-3,  1.8-2,  1.8-1,  1.8-0,  1.7.1-1,  1.7.1-0, 

1.8-6,  1.8-5,  1.8-4,  1.8-3,  1.8-2,  1.8-1,  1.8-0,  1.7.1-1,  1.7.1-0,  1.7-1,  1.7-0,  1.6-1,  1.6-0

depends bioconductor-biocstyle:

depends bioconductor-genomicranges:

depends bioconductor-rsamtools:

depends libgcc-ng:

>=12

depends libgfortran-ng:

depends libgfortran5:

>=12.2.0

depends libstdcxx-ng:

>=12

depends r-base:

>=4.2,<4.3.0a0

depends r-mvtnorm:

depends r-optparse:

depends r-rcpp:

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 r-histonehmm

and update with::

   mamba update r-histonehmm

To create a new environment, run:

mamba create --name myenvname r-histonehmm

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/r-histonehmm:<tag>

(see `r-histonehmm/tags`_ for valid values for ``<tag>``)

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Link to this page

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