recipe bioconductor-tdbasedufe

Tensor Decomposition Based Unsupervised Feature Extraction

Homepage:

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

License:

GPL-3

Recipe:

/bioconductor-tdbasedufe/meta.yaml

This is a comprehensive package to perform Tensor decomposition based unsupervised feature extraction. It can perform unsupervised feature extraction. It uses tensor decomposition. It is applicable to gene expression, DNA methylation, and histone modification etc. It can perform multiomics analysis. It is also potentially applicable to single cell omics data sets.

package bioconductor-tdbasedufe

versions:

1.6.0-0,  1.2.0-0,  1.0.0-0

depends bioconductor-genomicranges:

>=1.58.0,<1.59.0

depends bioconductor-mofadata:

>=1.22.0,<1.23.0

depends bioconductor-tximport:

>=1.34.0,<1.35.0

depends bioconductor-tximportdata:

>=1.34.0,<1.35.0

depends r-base:

>=4.4,<4.5.0a0

depends r-readr:

depends r-rtensor:

depends r-shiny:

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-tdbasedufe

and update with::

   mamba update bioconductor-tdbasedufe

To create a new environment, run:

mamba create --name myenvname bioconductor-tdbasedufe

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-tdbasedufe:<tag>

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

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