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/i4wnsw0ndqpp59bp830bggrm71zh66an-r-biosigner-1.20.0.drv | ||
powerpc64le-linux | /gnu/store/z574an962ynp1ji213idizph3gl3cayy-r-biosigner-1.20.0.drv | ||
mips64el-linux | /gnu/store/3knjv80p3v25g28361pmnqvsybsay9yb-r-biosigner-1.20.0.drv | ||
i686-linux | /gnu/store/bfrlgiijffa3mpg1dxqkkgkmwb4b61yr-r-biosigner-1.20.0.drv | ||
i586-gnu | /gnu/store/flqp2246x9qzgai0nhqjxac9mdn8nc9n-r-biosigner-1.20.0.drv | ||
armhf-linux | /gnu/store/h99i5w9654g4b4cv2z42rwi8gsrdfi6r-r-biosigner-1.20.0.drv | ||
aarch64-linux | /gnu/store/5jf26in365qn0spi0iyb972acl904cf7-r-biosigner-1.20.0.drv |
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