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
The integrative genomics viewer (IGV) is a pivotal tool in clinical genomics, enabling the visualization and interpretation of complex sequencing data. Bringing clinical knowledge to bear with visual evaluation of sequencing results is the primary means by which molecular pathologists and other professionals assess and...
E. Halper-Stromberg, Suguna P. Narayan, V. Laufer et al.· Journal of Visualized Experi...· 0 citations
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