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/pqc6pjvvgahardgjqszmk7pglndi2077-r-biosigner-1.18.2.drv | ||
powerpc64le-linux | /gnu/store/mja8dxaw6fpa73dqq7gm4aw70pywgns1-r-biosigner-1.18.2.drv | ||
mips64el-linux | /gnu/store/abj8zsbzy015pwmyjxgdihfbqbzwa02v-r-biosigner-1.18.2.drv | ||
i686-linux | /gnu/store/3lznc57az3addh49ngfq7shs6ya30bwh-r-biosigner-1.18.2.drv | ||
i586-gnu | /gnu/store/hjs2q71jc94k1rncimxlwcdkdy5wgqzf-r-biosigner-1.18.2.drv | ||
armhf-linux | /gnu/store/mykirixcxrqc5cqbrwjf0wixbb8708mz-r-biosigner-1.18.2.drv | ||
aarch64-linux | /gnu/store/wpb8lvm4zwg7ihr462jib4znf7qdcl5a-r-biosigner-1.18.2.drv |
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description Validate package descriptions | use @code or similar ornament instead of quotes |