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/2pc85a6q8h8zk0fs8ylmfkwf8bgnkxi6-r-biosigner-1.14.4.drv | ||
mips64el-linux | /gnu/store/87pvrd4m4f4nqvnhjvmy1qil5dh3linr-r-biosigner-1.14.4.drv | ||
i686-linux | /gnu/store/hf24lpngmdpb3wgh1dkrc0lzf8vjri46-r-biosigner-1.14.4.drv | ||
armhf-linux | /gnu/store/4pxwcvf20g88ral8vk6g3rz4mj75lca0-r-biosigner-1.14.4.drv | ||
aarch64-linux | /gnu/store/7hvx5shm6mhk7wm71rhisd8bv27agqxl-r-biosigner-1.14.4.drv |
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description Validate package descriptions | use @code or similar ornament instead of quotes |