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/cndd3mlqf8p0kfapyv1qb2zg587qha6s-r-biosigner-1.18.2.drv | ||
powerpc64le-linux | /gnu/store/as1w4dykjz0iqp4dd6m8y5jkn38g99as-r-biosigner-1.18.2.drv | ||
mips64el-linux | /gnu/store/ci2gzjfm0myj0z75y0sxl6x2gnsdskfs-r-biosigner-1.18.2.drv | ||
i686-linux | /gnu/store/9mdhfbq8d4dk3kkclw7ndwlkxc49p4xw-r-biosigner-1.18.2.drv | ||
i586-gnu | /gnu/store/5nhqi3z1vr07afi5cv54bhf0r6wzf87a-r-biosigner-1.18.2.drv | ||
armhf-linux | /gnu/store/9hyvbiphfl546bh6b2wx6aylkdz5gq3s-r-biosigner-1.18.2.drv | ||
aarch64-linux | /gnu/store/lgkzpasspjmvn3rw92jvkldpcny8d90k-r-biosigner-1.18.2.drv |
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