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/bv7b4mjbbbzq1vlgajk84wx6kwvyasxn-r-biosigner-1.18.2.drv | ||
powerpc64le-linux | /gnu/store/wywzxa761i2311f7kzzy3b0c8zfs2m6q-r-biosigner-1.18.2.drv | ||
mips64el-linux | /gnu/store/hzwwrh2x0hl31imzwz28yflpbzpvv2km-r-biosigner-1.18.2.drv | ||
i686-linux | /gnu/store/vbhhygwh6zqfz3aqhk2bawabrcjrvqri-r-biosigner-1.18.2.drv | ||
i586-gnu | /gnu/store/2a2156smb0w3wr7fsxaj471hbdpqmbiq-r-biosigner-1.18.2.drv | ||
armhf-linux | /gnu/store/z782jiqrfq0gv8674m0plpc3xjzwnym4-r-biosigner-1.18.2.drv | ||
aarch64-linux | /gnu/store/ix3w83731iim89mc3r8xrmnqlxap1yij-r-biosigner-1.18.2.drv |
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