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/gmvnza7lr4h1paaabnfmxr5hlk5n14ai-r-biosigner-1.18.2.drv | ||
mips64el-linux | /gnu/store/wmys9dh5zj6g3w11c5fgz7vc1z1fqf75-r-biosigner-1.18.2.drv | ||
i686-linux | /gnu/store/55dmmf4s6gp5mn12m9z35vazckbxcr89-r-biosigner-1.18.2.drv | ||
i586-gnu | /gnu/store/kp18dj9ny52pjfnpskzjglizkdq3cj85-r-biosigner-1.18.2.drv | ||
armhf-linux | /gnu/store/c9waf4cq2n7vrhfq60pznqalaq4cj2zc-r-biosigner-1.18.2.drv | ||
aarch64-linux | /gnu/store/4xf3c8swjy9np34mwafsjznygcchy4rd-r-biosigner-1.18.2.drv |
Linter | Message | Location |
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description Validate package descriptions | use @code or similar ornament instead of quotes |