recipe bioconductor-geneexpressionsignature

Gene Expression Signature based Similarity Metric

Homepage:

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

License:

GPL-2

Recipe:

/bioconductor-geneexpressionsignature/meta.yaml

This package gives the implementations of the gene expression signature and its distance to each. Gene expression signature is represented as a list of genes whose expression is correlated with a biological state of interest. And its distance is defined using a nonparametric, rank-based pattern-matching strategy based on the Kolmogorov-Smirnov statistic. Gene expression signature and its distance can be used to detect similarities among the signatures of drugs, diseases, and biological states of interest.

package bioconductor-geneexpressionsignature

(downloads) docker_bioconductor-geneexpressionsignature

versions:
1.52.0-01.48.0-01.46.0-01.44.0-01.40.0-01.38.0-01.34.0-01.32.0-01.30.0-1

1.52.0-01.48.0-01.46.0-01.44.0-01.40.0-01.38.0-01.34.0-01.32.0-01.30.0-11.28.0-0

depends bioconductor-biobase:

>=2.66.0,<2.67.0

depends r-base:

>=4.4,<4.5.0a0

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 bioconductor-geneexpressionsignature

and update with::

   mamba update bioconductor-geneexpressionsignature

To create a new environment, run:

mamba create --name myenvname bioconductor-geneexpressionsignature

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-geneexpressionsignature:<tag>

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

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