recipe r-diffcorr

A method for identifying pattern changes between 2 experimental conditions in correlation networks (e.g., gene co-expression networks), which builds on a commonly used association measure, such as Pearson's correlation coefficient. This package includes functions to calculate correlation matrices for high-dimensional dataset and to test differential correlation, which means the changes in the correlation relationship among variables (e.g., genes and metabolites) between 2 experimental conditions.

Homepage:

https://CRAN.R-project.org/package=DiffCorr

License:

GPL3 / GPL3

Recipe:

/r-diffcorr/meta.yaml

package r-diffcorr

(downloads) docker_r-diffcorr

versions:
0.4.4-0,  0.4.3-0,  0.4.2-2,  0.4.2-1,  0.4.2-0,  0.4.1-6,  0.4.1-5,  0.4.1-4,  0.4.1-3, 

0.4.4-0,  0.4.3-0,  0.4.2-2,  0.4.2-1,  0.4.2-0,  0.4.1-6,  0.4.1-5,  0.4.1-4,  0.4.1-3,  0.4.1-2,  0.4.1-1,  0.4.1-0

depends bioconductor-multtest:

depends bioconductor-pcamethods:

depends r-base:

>=4.3,<4.4.0a0

depends r-fdrtool:

depends r-igraph:

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 r-diffcorr

and update with::

   mamba update r-diffcorr

To create a new environment, run:

mamba create --name myenvname r-diffcorr

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-diffcorr:<tag>

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

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Link to this page

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