Package Recipe 'bioconductor-mosbi'

recipe bioconductor-mosbi

Molecular Signature identification using Biclustering

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/mosbi.html
License:: AGPL-3 + file LICENSE
Recipe:: /bioconductor-mosbi/meta.yaml

This package is a implementation of biclustering ensemble method MoSBi (Molecular signature Identification from Biclustering). MoSBi provides standardized interfaces for biclustering results and can combine their results with a multi-algorithm ensemble approach to compute robust ensemble biclusters on molecular omics data. This is done by computing similarity networks of biclusters and filtering for overlaps using a custom error model. After that, the louvain modularity it used to extract bicluster communities from the similarity network, which can then be converted to ensemble biclusters. Additionally, MoSBi includes several network visualization methods to give an intuitive and scalable overview of the results. MoSBi comes with several biclustering algorithms, but can be easily extended to new biclustering algorithms.

package bioconductor-mosbi¶

Versions:

1.16.0-0, 1.12.0-0, 1.8.0-0, 1.6.0-0, 1.4.0-1, 1.4.0-0, 1.0.3-1, 1.0.3-0, 1.0.0-0

Depends:

on bioconductor-fabia >=2.56.0,<2.57.0
on bioconductor-fabia >=2.56.0,<2.57.0a0
on bioconductor-qubic >=1.38.0,<1.39.0
on bioconductor-qubic >=1.38.0,<1.39.0a0
on libblas >=3.9.0,<4.0a0
on libgcc >=14
on liblapack >=3.9.0,<4.0a0
on liblzma >=5.8.2,<6.0a0
on libstdcxx >=14
on libzlib >=1.3.1,<2.0a0
on r-akmbiclust
on r-base >=4.5,<4.6.0a0
on r-bh
on r-biclust
on r-igraph
on r-isa2
on r-rcolorbrewer
on r-rcpp
on r-rcppparallel
on r-xml2
on tbb-devel >=2022.3.0,<2022.4.0a0

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-mosbi

to add into an existing workspace instead, run:

pixi add bioconductor-mosbi

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-mosbi

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-mosbi

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/bioconductor-mosbi:<tag>

(see bioconductor-mosbi/tags for valid values for <tag>).

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an 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-mosbi/README.html)