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/6kv766ixi7qhb3mwskg95j78a2fawlrm-r-biosigner-1.18.2.drv | ||
mips64el-linux | /gnu/store/jx861jhd9r5d60fpwc0mcx2jr78b7p83-r-biosigner-1.18.2.drv | ||
i686-linux | /gnu/store/6h4pp4x7aprjgd8i81nbn3h4vbqsvx2v-r-biosigner-1.18.2.drv | ||
i586-gnu | /gnu/store/bbcy20wr54c41wzyxdz1ngvj3wnivpx6-r-biosigner-1.18.2.drv | ||
armhf-linux | /gnu/store/ljkb8llq15cq72d0n3hqndrig821j1fr-r-biosigner-1.18.2.drv | ||
aarch64-linux | /gnu/store/x25v7sif62i5rn0znyw5kc5pc9q7l1a5-r-biosigner-1.18.2.drv |
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description Validate package descriptions | use @code or similar ornament instead of quotes |