recipe bioconductor-mlseq

Machine Learning Interface for RNA-Seq Data

Homepage:

https://bioconductor.org/packages/3.17/bioc/html/MLSeq.html

License:

GPL(>=2)

Recipe:

/bioconductor-mlseq/meta.yaml

Links:

biotools: mlseq, doi: 10.1038/nmeth.3252

This package applies several machine learning methods, including SVM, bagSVM, Random Forest and CART to RNA-Seq data.

package bioconductor-mlseq

versions:

2.18.0-0,  2.16.0-0,  2.12.0-0,  2.10.0-0,  2.8.0-1,  2.8.0-0,  2.6.0-0,  2.4.0-0,  2.2.1-1, 

2.18.0-0,  2.16.0-0,  2.12.0-0,  2.10.0-0,  2.8.0-1,  2.8.0-0,  2.6.0-0,  2.4.0-0,  2.2.1-1,  2.0.0-0,  1.20.3-0,  1.18.0-0

depends bioconductor-biobase:

>=2.60.0,<2.61.0

depends bioconductor-deseq2:

>=1.40.0,<1.41.0

depends bioconductor-edger:

>=3.42.0,<3.43.0

depends bioconductor-limma:

>=3.56.0,<3.57.0

depends bioconductor-sseq:

>=1.38.0,<1.39.0

depends bioconductor-summarizedexperiment:

>=1.30.0,<1.31.0

depends r-base:

>=4.3,<4.4.0a0

depends r-caret:

depends r-foreach:

depends r-ggplot2:

depends r-pamr:

depends r-plyr:

depends r-testthat:

depends r-venndiagram:

depends r-xtable:

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-mlseq

and update with::

   mamba update bioconductor-mlseq

To create a new environment, run:

mamba create --name myenvname bioconductor-mlseq

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-mlseq:<tag>

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

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