Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: application to cancer molecular classification

Background One major goal of large-scale cancer omics study is to identify molecular subtypes for more accurate cancer diagnoses and treatments. To deal with high-dimensional cancer multi-omics data, a promising strategy is to find an effective low-dimensional subspace of the original data and then...

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