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/8bf0v6lphqy4q54l7gwvg710wg2kqrw5-r-biosigner-1.18.2.drv | ||
powerpc64le-linux | /gnu/store/s4m26kzc6vzqmv7vgxm6rvphn62iyhg5-r-biosigner-1.18.2.drv | ||
mips64el-linux | /gnu/store/r36vf59wfqr3njcbyylhfd2s2pi9l25r-r-biosigner-1.18.2.drv | ||
i686-linux | /gnu/store/8y4scpl1s7yj5an0bm7jldm5xwwjrpcl-r-biosigner-1.18.2.drv | ||
i586-gnu | /gnu/store/ybcqhw620swd348vwr42py7hvzgv1ifw-r-biosigner-1.18.2.drv | ||
armhf-linux | /gnu/store/94m1h5xf2swc1bh4ldqicpns932kl611-r-biosigner-1.18.2.drv | ||
aarch64-linux | /gnu/store/k777xyvgfc4c1y2fx94gswcs42baav7p-r-biosigner-1.18.2.drv |
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