recipe bioconductor-qubic

An R package for qualitative biclustering in support of gene co-expression analyses

Homepage:

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

License:

CC BY-NC-ND 4.0 + file LICENSE

Recipe:

/bioconductor-qubic/meta.yaml

The core function of this R package is to provide the implementation of the well-cited and well-reviewed QUBIC algorithm, aiming to deliver an effective and efficient biclustering capability. This package also includes the following related functions: (i) a qualitative representation of the input gene expression data, through a well-designed discretization way considering the underlying data property, which can be directly used in other biclustering programs; (ii) visualization of identified biclusters using heatmap in support of overall expression pattern analysis; (iii) bicluster-based co-expression network elucidation and visualization, where different correlation coefficient scores between a pair of genes are provided; and (iv) a generalize output format of biclusters and corresponding network can be freely downloaded so that a user can easily do following comprehensive functional enrichment analysis (e.g. DAVID) and advanced network visualization (e.g. Cytoscape).

package bioconductor-qubic

versions:

1.30.0-0,  1.28.0-0,  1.26.0-2,  1.26.0-1,  1.26.0-0,  1.22.0-2,  1.22.0-1,  1.22.0-0,  1.20.0-0, 

1.30.0-0,  1.28.0-0,  1.26.0-2,  1.26.0-1,  1.26.0-0,  1.22.0-2,  1.22.0-1,  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

depends libblas:

>=3.9.0,<4.0a0

depends libgcc-ng:

>=12

depends liblapack:

>=3.9.0,<4.0a0

depends libstdcxx-ng:

>=12

depends r-base:

>=4.3,<4.4.0a0

depends r-biclust:

depends r-matrix:

depends r-rcpp:

>=0.11.0

depends r-rcpparmadillo:

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-qubic

and update with::

   mamba update bioconductor-qubic

To create a new environment, run:

mamba create --name myenvname bioconductor-qubic

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-qubic:<tag>

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

Download stats

Link to this page

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