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/vrq7hrms9vjdhykads8sghvkk0wqwk8h-r-biosigner-1.14.4.drv | ||
mips64el-linux | /gnu/store/36n6bwzs2bz3g1lzi8lxxvh4spnp1a88-r-biosigner-1.14.4.drv | ||
i686-linux | /gnu/store/m932c8svdsrpmsiq34wmy66jmqffc3dh-r-biosigner-1.14.4.drv | ||
i586-gnu | /gnu/store/1cxfmf60p0h2z0m3ppihzq1d8ychpg4b-r-biosigner-1.14.4.drv | ||
armhf-linux | /gnu/store/g9cbmcihixbb8ivhl4y50hi8z0ni72hq-r-biosigner-1.14.4.drv | ||
aarch64-linux | /gnu/store/jlz33gf017whx15qafa8s9iapwkawzkk-r-biosigner-1.14.4.drv |
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description Validate package descriptions | use @code or similar ornament instead of quotes |