Identification of Tumor Subtypes of Endometrial Carcinoma by Integration of Heterogeneous Datasets

Clustering algorithms have been applied to the identification of new subtypes of human cancer. Clustering of heterogeneous datasets represents a difficult clustering problem to which some clustering methods cannot be easily extended. Clustering methods based on matrix computations, such as non-negative matrix factorization (NMF), can be modified to deal with this complex problem. In this paper, we will show how the formulation of NMF can be modified for tumor subtype identification with multiple heterogeneous datasets.