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What is Optimal ICA Components for Cancer Survival about?
This study investigated the optimal number of independent components (ICs) to extract from transcriptomics data for patient classification and survival prediction. The authors: 1) Analyzed how the number of ICs affects stability and reproducibility of decomposition on several cancer datasets. More ICs require larger sample sizes for stability. 2) Found optimal IC numbers for subtype prediction in different cancers: 20 for GMB-LGG, 60 for LUAD-LUSC and SKCM, 10 for PAAD. Prediction was better using ICs th
- Author
- azjajaoan malaya
- Language
- EN