recipe r-bisquerna

Provides tools to accurately estimate cell type abundances from heterogeneous bulk expression.

Homepage:

https://www.biorxiv.org/content/10.1101/669911v1

License:

GPL3 / GPL-3.0-only

Recipe:

/r-bisquerna/meta.yaml

A reference-based method utilizes single-cell information to generate a signature matrix and transformation of bulk expression for accurate regression based estimates. A marker-based method utilizes known cell-specific marker genes to measure relative abundances across samples. For more details, see Jew and Alvarez et al (2019) <doi:10.1101/669911>.

package r-bisquerna

(downloads) docker_r-bisquerna

versions:
1.0.5-3,  1.0.5-2,  1.0.5-1,  1.0.5-0,  1.0.4-2,  1.0.4-1,  1.0.4-0,  1.0.3-1,  1.0.3-0, 

1.0.5-3,  1.0.5-2,  1.0.5-1,  1.0.5-0,  1.0.4-2,  1.0.4-1,  1.0.4-0,  1.0.3-1,  1.0.3-0,  1.0.2-0,  1.0.1-0,  1.0-1,  1.0-0

depends bioconductor-biobase:

depends r-base:

>=4.4,<4.5.0a0

depends r-limsolve:

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-bisquerna

and update with::

   mamba update r-bisquerna

To create a new environment, run:

mamba create --name myenvname r-bisquerna

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-bisquerna:<tag>

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

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