Package Recipe 'bioconductor-mineica'

recipe bioconductor-mineica

Analysis of an ICA decomposition obtained on genomics data

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/MineICA.html
License:: GPL-2
Recipe:: /bioconductor-mineica/meta.yaml
Links:: biotools: mineica, doi: 10.1155/2014/213656

The goal of MineICA is to perform Independent Component Analysis (ICA) on multiple transcriptome datasets, integrating additional data (e.g molecular, clinical and pathological). This Integrative ICA helps the biological interpretation of the components by studying their association with variables (e.g sample annotations) and gene sets, and enables the comparison of components from different datasets using correlation-based graph.

package bioconductor-mineica¶

Versions:

1.49.0-0, 1.46.0-0, 1.42.0-0, 1.40.0-0, 1.38.0-0, 1.34.0-0, 1.32.0-0, 1.30.0-1, 1.30.0-0,

1.49.0-0, 1.46.0-0, 1.42.0-0, 1.40.0-0, 1.38.0-0, 1.34.0-0, 1.32.0-0, 1.30.0-1, 1.30.0-0, 1.28.0-0, 1.26.0-0, 1.24.0-1, 1.22.0-0, 1.18.0-0

Depends:

on bioconductor-annotate >=1.88.0,<1.89.0
on bioconductor-annotationdbi >=1.72.0,<1.73.0
on bioconductor-biobase >=2.70.0,<2.71.0
on bioconductor-biocgenerics >=0.56.0,<0.57.0
on bioconductor-biomart >=2.66.0,<2.67.0
on bioconductor-gostats >=2.76.0,<2.77.0
on bioconductor-graph >=1.88.0,<1.89.0
on bioconductor-lumi >=2.62.0,<2.63.0
on bioconductor-lumihumanall.db >=1.22.0,<1.23.0
on bioconductor-marray >=1.88.0,<1.89.0
on bioconductor-rgraphviz >=2.54.0,<2.55.0
on r-base >=4.5,<4.6.0a0
on r-cluster
on r-colorspace
on r-fastica
on r-foreach
on r-fpc
on r-ggplot2
on r-gtools
on r-hmisc
on r-igraph
on r-jade
on r-mclust
on r-plyr
on r-rcolorbrewer
on r-scales
on r-xtable

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-mineica

to add into an existing workspace instead, run:

pixi add bioconductor-mineica

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-mineica

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-mineica

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-mineica:<tag>

(see bioconductor-mineica/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-mineica/README.html)