recipe bioconductor-sgcp

SGCP: A semi-supervised pipeline for gene clustering using self-training approach in gene co-expression networks

Homepage:

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

License:

GPL-3

Recipe:

/bioconductor-sgcp/meta.yaml

SGC is a semi-supervised pipeline for gene clustering in gene co-expression networks. SGC consists of multiple novel steps that enable the computation of highly enriched modules in an unsupervised manner. But unlike all existing frameworks, it further incorporates a novel step that leverages Gene Ontology information in a semi-supervised clustering method that further improves the quality of the computed modules.

package bioconductor-sgcp

versions:

1.2.0-0,  1.0.0-0

depends bioconductor-annotate:

>=1.80.0,<1.81.0

depends bioconductor-genefilter:

>=1.84.0,<1.85.0

depends bioconductor-go.db:

>=3.18.0,<3.19.0

depends bioconductor-gostats:

>=2.68.0,<2.69.0

depends bioconductor-graph:

>=1.80.0,<1.81.0

depends bioconductor-org.hs.eg.db:

>=3.18.0,<3.19.0

depends bioconductor-rgraphviz:

>=2.46.0,<2.47.0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0

depends r-base:

>=4.3,<4.4.0a0

depends r-caret:

depends r-desctools:

depends r-dplyr:

depends r-expm:

depends r-ggplot2:

depends r-ggridges:

depends r-openxlsx:

depends r-plyr:

depends r-rcolorbrewer:

depends r-reshape2:

depends r-rspectra:

depends r-xtable:

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-sgcp

and update with::

   mamba update bioconductor-sgcp

To create a new environment, run:

mamba create --name myenvname bioconductor-sgcp

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-sgcp:<tag>

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

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