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/sjjcxadssid6l57k8jpgvkavphpyj7d1-r-biosigner-1.18.2.drv | ||
mips64el-linux | /gnu/store/ns2h67lmnp03wn7mys43qbl9zg54hvhm-r-biosigner-1.18.2.drv | ||
i686-linux | /gnu/store/nivcjsi9zciviz696wa5bgl32zvz9gl4-r-biosigner-1.18.2.drv | ||
i586-gnu | /gnu/store/c8m81xsapniwn1y9cfa79hz52sv8kp93-r-biosigner-1.18.2.drv | ||
armhf-linux | /gnu/store/xq6j5lb1af88myxs1l4y9lvpl483q1g1-r-biosigner-1.18.2.drv | ||
aarch64-linux | /gnu/store/7rb6fla8xsrsz6vihsnl58r0qf2k2l9q-r-biosigner-1.18.2.drv |
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description Validate package descriptions | use @code or similar ornament instead of quotes |