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/9hjfqs4c1ypms4pg3la9fz438da1avqv-r-biosigner-1.18.2.drv | ||
mips64el-linux | /gnu/store/a42y3ngv3vi8xs37n601mviambhfrs6w-r-biosigner-1.18.2.drv | ||
i686-linux | /gnu/store/lridjvm4scsi4d9ai5h037gy2m4mqw90-r-biosigner-1.18.2.drv | ||
i586-gnu | /gnu/store/2qc1xvwrgzmpx3grgvawrg4l571dmm70-r-biosigner-1.18.2.drv | ||
armhf-linux | /gnu/store/b6kvv2gaj3y4vpssa3rb00ciy5yx3rb6-r-biosigner-1.18.2.drv | ||
aarch64-linux | /gnu/store/am96xryylskm9acr8gwdrb4y9pwy9kmz-r-biosigner-1.18.2.drv |
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description Validate package descriptions | use @code or similar ornament instead of quotes |