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/nhkl3d3l38hzcaz4iicwg66x3mkbmpd8-r-biosigner-1.14.0.drv | ||
mips64el-linux | /gnu/store/cv08d3i4sxznjspgz52bc44vwpb805yv-r-biosigner-1.14.0.drv | ||
i686-linux | /gnu/store/hm9k75xpd1fndwxgxmw79d6w5fy4zkkc-r-biosigner-1.14.0.drv | ||
armhf-linux | /gnu/store/0qlkn0i2209a1izp8c129v6l3mn5xr2g-r-biosigner-1.14.0.drv | ||
aarch64-linux | /gnu/store/hmqsd5ckj9s5bqj3d7119y0x4p76gdxb-r-biosigner-1.14.0.drv |
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description Validate package descriptions | use @code or similar ornament instead of quotes |