recipe bioconductor-infercnv

Infer Copy Number Variation from Single-Cell RNA-Seq Data



BSD_3_clause + file LICENSE



Using single-cell RNA-Seq expression to visualize CNV in cells.

package bioconductor-infercnv

(downloads) docker_bioconductor-infercnv



depends bioconductor-biocgenerics:


depends bioconductor-edger:


depends bioconductor-singlecellexperiment:


depends bioconductor-summarizedexperiment:


depends jags:


depends r-ape:

depends r-argparse:

depends r-base:


depends r-catools:

depends r-coda:

depends r-coin:

depends r-digest:

depends r-doparallel:

depends r-dplyr:

depends r-fastcluster:

depends r-fitdistrplus:

depends r-foreach:

depends r-futile.logger:

depends r-future:

depends r-ggplot2:

depends r-gplots:

depends r-gridextra:

depends r-hiddenmarkov:

depends r-htmltools:


depends r-igraph:

depends r-matrix:

depends r-paralleldist:

depends r-phyclust:

depends r-rann:

depends r-rcolorbrewer:

depends r-reshape2:

depends r-rjags:

depends r-seurat:

depends r-tidyr:



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-infercnv

and update with::

   mamba update bioconductor-infercnv

To create a new environment, run:

mamba create --name myenvname bioconductor-infercnv

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

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