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 |
---|---|---|---|
x86_64-linux | /gnu/store/hpnv5jv8s9ks8dgqd53spb0j0cwwavda-r-biosigner-1.18.2.drv | ||
mips64el-linux | /gnu/store/qw6yjiqmj3mrqvfbpvfsfm9dzqfmgxqn-r-biosigner-1.18.2.drv | ||
i686-linux | /gnu/store/dhzpaqka03s4iba9s9yzwqkq3h86168l-r-biosigner-1.18.2.drv | ||
i586-gnu | /gnu/store/r4n84a85m6iz8lahhb0ad0j8jb59jn26-r-biosigner-1.18.2.drv | ||
armhf-linux | /gnu/store/6pf32kv5m3dfkrbyv7abdamhgv88wrrj-r-biosigner-1.18.2.drv | ||
aarch64-linux | /gnu/store/5v66axdfb7915lx88fhsgw6rvi67a6yd-r-biosigner-1.18.2.drv |
Linter | Message | Location |
---|---|---|
description Validate package descriptions | use @code or similar ornament instead of quotes |