recipe r-eacon

Easy Copy Number. EaCoN aims to be an all-packed in, user-friendly solution to perform relative or absolute copy-number analysis for multiple sources of data, with three different segmenters available (and corresponding three copy-number modelization methods)






package r-eacon

(downloads) docker_r-eacon



depends ascat:


depends bioconductor-affxparser:

depends bioconductor-aroma.light:

depends bioconductor-biostrings:

depends bioconductor-bsgenome.hsapiens.1000genomes.hs37d5:

depends bioconductor-copynumber:

depends bioconductor-genomicranges:

depends bioconductor-limma:

depends bioconductor-rhdf5:

depends bioconductor-rsamtools:

depends r-base:


depends r-bedr:

depends r-changepoint:

depends r-data.table:

depends r-doparallel:

depends r-dplyr:

depends r-dt:

depends r-facets:

depends r-foreach:

depends r-iotools:

depends r-mclust:

depends r-rmarkdown:

depends r-seqinr:

depends r-sequenza:



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-eacon

and update with::

   mamba update r-eacon

To create a new environment, run:

mamba create --name myenvname r-eacon

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<tag>

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

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