- recipe bioconductor-biosigner
Signature discovery from omics data
- Homepage
https://bioconductor.org/packages/3.14/bioc/html/biosigner.html
- License
CeCILL
- Recipe
- Links
biotools: biosigner, doi: 10.3389/fmolb.2016.00026
Feature selection is critical in omics data analysis to extract restricted and meaningful molecular signatures from complex and high-dimension data, and to build robust classifiers. This package implements a new method to assess the relevance of the variables for the prediction performances of the classifier. The approach can be run in parallel with the PLS-DA, Random Forest, and SVM binary classifiers. The signatures and the corresponding 'restricted' models are returned, enabling future predictions on new datasets. A Galaxy implementation of the package is available within the Workflow4metabolomics.org online infrastructure for computational metabolomics.
- package bioconductor-biosigner¶
-
- Versions
1.22.0-0
,1.20.0-0
,1.18.2-0
,1.18.0-0
,1.16.0-0
,1.14.0-0
,1.12.0-1
,1.10.0-0
,1.8.0-0
,1.22.0-0
,1.20.0-0
,1.18.2-0
,1.18.0-0
,1.16.0-0
,1.14.0-0
,1.12.0-1
,1.10.0-0
,1.8.0-0
,1.6.0-0
,1.4.0-0
,1.1.10-0
,1.0.6-0
- Depends
bioconductor-biobase
>=2.54.0,<2.55.0
bioconductor-multidataset
>=1.22.0,<1.23.0
bioconductor-ropls
>=1.26.0,<1.27.0
r-base
>=4.1,<4.2.0a0
- Required By
Installation
With an activated Bioconda channel (see 2. Set up channels), install with:
conda install bioconductor-biosigner
and update with:
conda update bioconductor-biosigner
or use the docker container:
docker pull quay.io/biocontainers/bioconductor-biosigner:<tag>
(see bioconductor-biosigner/tags for valid values for
<tag>
)
Download stats¶
Link to this page¶
Render an badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-biosigner/README.html)