recipe r-conos

Wires together large collections of single-cell RNA-seq datasets, which allows for both the identification of recurrent cell clusters and the propagation of information between datasets in multi-sample or atlas-scale collections. 'Conos' focuses on the uniform mapping of homologous cell types across heterogeneous sample collections. For instance, users could investigate a collection of dozens of peripheral blood samples from cancer patients combined with dozens of controls, which perhaps includes samples of a related tissue such as lymph nodes. This package interacts with data available through the 'conosPanel' package, which is available in a 'drat' repository. To access this data package, see the instructions at <https://github.com/kharchenkolab/conos>. The size of the 'conosPanel' package is approximately 12 MB.

Homepage:

https://github.com/kharchenkolab/conos

License:

GPL3 / GPL-3.0-only

Recipe:

/r-conos/meta.yaml

package r-conos

versions:

1.5.2-1,  1.5.2-0,  1.5.1-0,  1.5.0-3,  1.5.0-2,  1.5.0-1,  1.5.0-0,  1.4.9-0,  1.4.8-0, 

1.5.2-1,  1.5.2-0,  1.5.1-0,  1.5.0-3,  1.5.0-2,  1.5.0-1,  1.5.0-0,  1.4.9-0,  1.4.8-0,  1.4.7-0,  1.4.6-0

depends bioconductor-complexheatmap:

>=2.22.0,<2.23.0a0

depends libgcc:

>=13

depends libstdcxx:

>=13

depends r-abind:

depends r-base:

>=4.4,<4.5.0a0

depends r-cowplot:

depends r-dendextend:

depends r-dplyr:

depends r-ggplot2:

depends r-ggrepel:

depends r-gridextra:

depends r-igraph:

depends r-irlba:

depends r-leidenalg:

depends r-magrittr:

depends r-matrix:

depends r-n2r:

depends r-r6:

depends r-rcpp:

depends r-rcpparmadillo:

depends r-rcppeigen:

depends r-rcppprogress:

depends r-reshape2:

depends r-rlang:

depends r-rtsne:

depends r-sccore:

>=1.0.0

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-conos

and update with::

   mamba update r-conos

To create a new environment, run:

mamba create --name myenvname r-conos

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-conos:<tag>

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

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