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Cancer-related genes: dimension reduction model for cell-line genomic data

for the input of a machine learning model I am designing, I use cell-line gene expression data and cell-line mutation data from CCLE. However, I want to first reduce the input dimension (number of genes) because that I believe that not all the genes are related to cancer. how can I find a pre-trained model that reduces the number of genes in the cancer cell-lines model? (each of mutation data and expression data). I was implementing it by an autoencoder, but I thought there must be a study that precisely worked on finding cancer-related genes in mutation or expression data, and it's better to use that study model.

ccle expression mutation_data cancer_genes dimention_reduction

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