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/3jpmaypl0a1rajfn8qg06dzzcy7j7wnw-r-biosigner-1.18.2.drv | ||
mips64el-linux | /gnu/store/gx0np6n6362jqrw0lzgs21q3b08y1pim-r-biosigner-1.18.2.drv | ||
i686-linux | /gnu/store/7gk4li09hwzgkry3vmqbvz4l3pmk43vz-r-biosigner-1.18.2.drv | ||
i586-gnu | /gnu/store/j6lic5nvcyyyjlpklr4j3z0k1lldr1dg-r-biosigner-1.18.2.drv | ||
armhf-linux | /gnu/store/8kks0pqjvd9500njlwls6xgp9rrfpidg-r-biosigner-1.18.2.drv | ||
aarch64-linux | /gnu/store/wam2c7kbma30c8xbkckvl51g8mg2f3p0-r-biosigner-1.18.2.drv |
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