recipe bioconductor-clustersignificance

The ClusterSignificance package provides tools to assess if class clusters in dimensionality reduced data representations have a separation different from permuted data

Homepage:

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

License:

GPL-3

Recipe:

/bioconductor-clustersignificance/meta.yaml

Links:

biotools: clustersignificance, doi: 10.1038/nmeth.3252

The ClusterSignificance package provides tools to assess if class clusters in dimensionality reduced data representations have a separation different from permuted data. The term class clusters here refers to, clusters of points representing known classes in the data. This is particularly useful to determine if a subset of the variables, e.g. genes in a specific pathway, alone can separate samples into these established classes. ClusterSignificance accomplishes this by, projecting all points onto a one dimensional line. Cluster separations are then scored and the probability of the seen separation being due to chance is evaluated using a permutation method.

package bioconductor-clustersignificance

versions:

1.30.0-0,  1.28.0-0,  1.26.0-0,  1.22.0-0,  1.20.0-0,  1.18.0-1,  1.18.0-0,  1.16.0-0,  1.14.0-0, 

1.30.0-0,  1.28.0-0,  1.26.0-0,  1.22.0-0,  1.20.0-0,  1.18.0-1,  1.18.0-0,  1.16.0-0,  1.14.0-0,  1.12.0-1,  1.12.0-0,  1.10.0-0,  1.8.2-0,  1.6.0-0

depends r-base:

>=4.3,<4.4.0a0

depends r-pracma:

depends r-princurve:

>=2.0.5

depends r-rcolorbrewer:

depends r-scatterplot3d:

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-clustersignificance

and update with::

   mamba update bioconductor-clustersignificance

To create a new environment, run:

mamba create --name myenvname bioconductor-clustersignificance

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-clustersignificance:<tag>

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

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