recipe bioconductor-sigfeature

sigFeature: Significant feature selection using SVM-RFE & t-statistic

Homepage:

https://bioconductor.org/packages/3.16/bioc/html/sigFeature.html

License:

GPL (>= 2)

Recipe:

/bioconductor-sigfeature/meta.yaml

This package provides a novel feature selection algorithm for binary classification using support vector machine recursive feature elimination SVM-RFE and t-statistic. In this feature selection process, the selected features are differentially significant between the two classes and also they are good classifier with higher degree of classification accuracy.

package bioconductor-sigfeature

Versions:

1.16.0-0,  1.12.0-0,  1.10.0-0,  1.8.0-1,  1.8.0-0,  1.6.0-0,  1.4.0-0,  1.2.0-1,  1.0.0-0

Depends:

• bioconductor-biocparallel >=1.32.0,<1.33.0

• bioconductor-biocviews >=1.66.0,<1.67.0

• bioconductor-summarizedexperiment >=1.28.0,<1.29.0

• r-base >=4.2,<4.3.0a0

• r-e1071

• r-matrix

• r-nlme

• r-openxlsx

• r-pheatmap

• r-rcolorbrewer

• r-sparsem

Required By:

Installation

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

conda install bioconductor-sigfeature

and update with:

conda update bioconductor-sigfeature

or use the docker container:

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

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

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-sigfeature/README.html)