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/m3cxrvmscgkkvcs8iy5ilpjyqcpnz8p2-r-biosigner-1.18.2.drv | ||
powerpc64le-linux | /gnu/store/q3i024dqb4z98c5sijf0vqp1k825rgvd-r-biosigner-1.18.2.drv | ||
mips64el-linux | /gnu/store/n5bib21jkpa4gicrjkbiaamdv0nk70yl-r-biosigner-1.18.2.drv | ||
i686-linux | /gnu/store/r238g3q3xmywwwachsw1rvmg8vryp0k4-r-biosigner-1.18.2.drv | ||
i586-gnu | /gnu/store/h3an9xxc9mddnksf2cj33ciy6ndsjl4i-r-biosigner-1.18.2.drv | ||
armhf-linux | /gnu/store/nfhxsic5ncv7ky2js6i08wjqv0bgw9gv-r-biosigner-1.18.2.drv | ||
aarch64-linux | /gnu/store/qikdnjqlfbpcw2q0d8frb3dcadxrrzph-r-biosigner-1.18.2.drv |
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