recipe r-cdseq

Estimate cell-type-specific gene expression profiles and sample-specific cell-type proportions simultaneously using bulk sequencing data. Kang et al. (2019) <doi:10.1371/journal.pcbi.1007510>.

Homepage:

https://github.com/omnideconv/CDSeq

License:

GPL / GPL-3

Recipe:

/r-cdseq/meta.yaml

Links:

doi: 10.1371/journal.pcbi.1007510

package r-cdseq

versions:

0-6,  0-5,  0-3,  0-2,  0-1,  0-0

depends bioconductor-biobase:

>=2.66.0,<2.67.0a0

depends libgcc:

>=13

depends libstdcxx:

>=13

depends r-base:

>=4.4,<4.5.0a0

depends r-clue:

depends r-dirmult:

depends r-doparallel:

depends r-dplyr:

depends r-foreach:

depends r-ggplot2:

depends r-ggpubr:

depends r-gplots:

depends r-harmony:

depends r-iterators:

depends r-magrittr:

depends r-mass:

depends r-matrix:

depends r-matrixstats:

depends r-pheatmap:

depends r-qlcmatrix:

depends r-rcpp:

>=1.0.3

depends r-rcppthread:

depends r-rlang:

depends r-seurat:

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-cdseq

and update with::

   mamba update r-cdseq

To create a new environment, run:

mamba create --name myenvname r-cdseq

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-cdseq:<tag>

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

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