Signature discovery from omics data
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 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.
System | Target | Derivation | Build status |
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x86_64-linux | /gnu/store/bwimggcakw5b6n4c662za6snrdxrsc9x-r-biosigner-1.18.2.drv | ||
powerpc64le-linux | /gnu/store/kf2wqq72ja70iqkc0f759ni5zlyjdb6q-r-biosigner-1.18.2.drv | ||
mips64el-linux | /gnu/store/iys0f3m82kcxs7z09320f7ci9cn6srni-r-biosigner-1.18.2.drv | ||
i686-linux | /gnu/store/rhnay62s08a9l44dapf0zp8cxj08fdlq-r-biosigner-1.18.2.drv | ||
i586-gnu | /gnu/store/wg5l4458i6nxcjvhvv4laknq4aiy9w6x-r-biosigner-1.18.2.drv | ||
armhf-linux | /gnu/store/8yj67k8fy0v3vc1kbcg88kahch3lgs1r-r-biosigner-1.18.2.drv | ||
aarch64-linux | /gnu/store/fzcrffvdx8fbv01q6ihp55ipl19wigk4-r-biosigner-1.18.2.drv |
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