bioconda / packages / bioconductor-biosigner 1.10.0

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.

Installers

Info: This package contains files in non-standard labels.

conda install

  • linux-64  v1.8.0
  • osx-64  v1.8.0
  • noarch  v1.10.0
To install this package with conda run one of the following:
conda install -c bioconda bioconductor-biosigner
conda install -c bioconda/label/gcc7 bioconductor-biosigner
conda install -c bioconda/label/cf201901 bioconductor-biosigner

Description

PRIVACY POLICY  |  EULA (Anaconda Cloud v2.33.29) © 2019 Anaconda, Inc. All Rights Reserved.