recipe bioconductor-cnvmetrics

Copy Number Variant Metrics






The CNVMetrics package calculates similarity metrics to facilitate copy number variant comparison among samples and/or methods. Similarity metrics can be employed to compare CNV profiles of genetically unrelated samples as well as those with a common genetic background. Some metrics are based on the shared amplified/deleted regions while other metrics rely on the level of amplification/deletion. The data type used as input is a plain text file containing the genomic position of the copy number variations, as well as the status and/or the log2 ratio values. Finally, a visualization tool is provided to explore resulting metrics.

package bioconductor-cnvmetrics

(downloads) docker_bioconductor-cnvmetrics



depends bioconductor-biocparallel:


depends bioconductor-genomicranges:


depends bioconductor-iranges:


depends bioconductor-s4vectors:


depends r-base:


depends r-gridextra:

depends r-magrittr:

depends r-pheatmap:

depends r-rbeta2009:



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 bioconductor-cnvmetrics

and update with::

   mamba update bioconductor-cnvmetrics

To create a new environment, run:

mamba create --name myenvname bioconductor-cnvmetrics

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 `bioconductor-cnvmetrics/tags`_ for valid values for ``<tag>``)

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