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

Kim H, Bredel M, Park H, Ch

Abstract

The Cancer Genome Atlas (TCGA) project has made available multiple heterogeneous datasets. Although several methodological approaches have been proposed for the heterogeneous data integration, there is no framework of sparse non-negative matrix factorization (NMF) for handling heterogeneous biological data integration. Here, we propose the block-weighted sparse NMF bwsNMF) to identify tumor subtypes of endometrial carcinoma by integrating gene expression, mutations, a protein-protein interaction network and a transcription factor target network.