recipe bioconductor-deconrnaseq

Deconvolution of Heterogeneous Tissue Samples for mRNA-Seq data

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/DeconRNASeq.html

License:

GPL-2

Recipe:

/bioconductor-deconrnaseq/meta.yaml

DeconSeq is an R package for deconvolution of heterogeneous tissues based on mRNA-Seq data. It modeled expression levels from heterogeneous cell populations in mRNA-Seq as the weighted average of expression from different constituting cell types and predicted cell type proportions of single expression profiles.

package bioconductor-deconrnaseq

(downloads) docker_bioconductor-deconrnaseq

versions:
1.44.0-01.42.0-01.40.0-01.36.0-01.34.0-01.32.0-11.32.0-01.30.0-01.28.0-0

1.44.0-01.42.0-01.40.0-01.36.0-01.34.0-01.32.0-11.32.0-01.30.0-01.28.0-01.26.0-11.24.0-11.24.0-0

depends bioconductor-pcamethods:

>=1.94.0,<1.95.0

depends r-base:

>=4.3,<4.4.0a0

depends r-ggplot2:

depends r-limsolve:

requirements:

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 bioconductor-deconrnaseq

and update with::

   mamba update bioconductor-deconrnaseq

To create a new environment, run:

mamba create --name myenvname bioconductor-deconrnaseq

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/bioconductor-deconrnaseq:<tag>

(see `bioconductor-deconrnaseq/tags`_ for valid values for ``<tag>``)

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