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Integrative Analysis Of Survival-Associated Gene Sets In Breast Cancer, Frederick S. Varn, Matthew H. Ung, Shao Ke Lou, Chao Cheng

Dartmouth Scholarship

Patient gene expression information has recently become a clinical feature used to evaluate breast cancer prognosis. The emergence of prognostic gene sets that take advantage of these data has led to a rich library of information that can be used to characterize the molecular nature of a patient’s cancer. Identifying robust gene sets that are consistently predictive of a patient’s clinical outcome has become one of the main challenges in the field. We inputted our previously established BASE algorithm with patient gene expression data and gene sets from MSigDB to develop the gene set activity score (GSAS), a metric that …