recipe bioconductor-mlseq

Machine Learning Interface for RNA-Seq Data

Homepage:

https://bioconductor.org/packages/3.16/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:

2.16.0-0,  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, 

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 >=2.58.0,<2.59.0

• bioconductor-deseq2 >=1.38.0,<1.39.0

• bioconductor-edger >=3.40.0,<3.41.0

• bioconductor-limma >=3.54.0,<3.55.0

• bioconductor-sseq >=1.36.0,<1.37.0

• bioconductor-summarizedexperiment >=1.28.0,<1.29.0

• r-base >=4.2,<4.3.0a0

• r-caret

• r-foreach

• r-ggplot2

• r-pamr

• r-plyr

• r-testthat

• r-venndiagram

• r-xtable

Required By:

• bioconductor-gars

Installation

With an activated Bioconda channel (see set-up-channels), install with:

conda install bioconductor-mlseq

and update with:

conda update bioconductor-mlseq

or 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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