Cancer genomic analyses increasingly involve large, complex datasets representing diverse ‘omics’ variables, such as gene expression, mutations, copy number alterations, genetic perturbations (e.g. CRISPR or iRNA), drug sensitivity, and clinical phenotypes, making it crucial to accurately measure associations among the...
Timothy Pham, Karina Meneses-Cime, Jia-Yan Ma et al.· bioRxiv· 0 citations
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