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/7sgzbylz9hjd58gd2mgw3vxngr0i2mi2-r-biosigner-1.14.0.drv | ||
mips64el-linux | /gnu/store/hsrjd5syrwrpa8lvbk4w4vg9ph9mryxq-r-biosigner-1.14.0.drv | ||
i686-linux | /gnu/store/49ybd1rpci5m4pl0fb179vm46d0im3p1-r-biosigner-1.14.0.drv | ||
armhf-linux | /gnu/store/z6hw2z4pndnphkg8901fsdnp98kaaysy-r-biosigner-1.14.0.drv | ||
aarch64-linux | /gnu/store/cf983116mcnfnxnqxnss0k1q9xz9fa58-r-biosigner-1.14.0.drv |
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description Validate package descriptions | use @code or similar ornament instead of quotes |