recipe bioconductor-rscudo

Signature-based Clustering for Diagnostic Purposes

Homepage:

https://bioconductor.org/packages/3.20/bioc/html/rScudo.html

License:

GPL-3

Recipe:

/bioconductor-rscudo/meta.yaml

SCUDO (Signature-based Clustering for Diagnostic Purposes) is a rank-based method for the analysis of gene expression profiles for diagnostic and classification purposes. It is based on the identification of sample-specific gene signatures composed of the most up- and down-regulated genes for that sample. Starting from gene expression data, functions in this package identify sample-specific gene signatures and use them to build a graph of samples. In this graph samples are joined by edges if they have a similar expression profile, according to a pre-computed similarity matrix. The similarity between the expression profiles of two samples is computed using a method similar to GSEA. The graph of samples can then be used to perform community clustering or to perform supervised classification of samples in a testing set.

package bioconductor-rscudo

(downloads) docker_bioconductor-rscudo

versions:
1.22.0-0,  1.18.0-0,  1.16.0-0,  1.14.0-0,  1.10.0-0,  1.8.0-0,  1.6.0-1,  1.6.0-0,  1.4.0-0, 

1.22.0-0,  1.18.0-0,  1.16.0-0,  1.14.0-0,  1.10.0-0,  1.8.0-0,  1.6.0-1,  1.6.0-0,  1.4.0-0,  1.2.0-0,  1.0.0-1

depends bioconductor-biobase:

>=2.66.0,<2.67.0

depends bioconductor-biocgenerics:

>=0.52.0,<0.53.0

depends bioconductor-s4vectors:

>=0.44.0,<0.45.0

depends bioconductor-summarizedexperiment:

>=1.36.0,<1.37.0

depends r-base:

>=4.4,<4.5.0a0

depends r-igraph:

depends r-stringr:

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-rscudo

and update with::

   mamba update bioconductor-rscudo

To create a new environment, run:

mamba create --name myenvname bioconductor-rscudo

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-rscudo:<tag>

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

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Link to this page

Render an install-with-bioconda badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-rscudo/README.html)