Article

Pan-cancer identification of clinically relevant genomic subtypes using outcome-weighted integrative clustering

2020-05-12

Abstract excerpt

<h4>ABSTRACT</h4> Molecular phenotypes of cancer are complex and influenced by a multitude of factors. Conventional unsupervised clustering of heterogeneous cancer patient populations is inevitably driven by the dominant variation from major factors such as cell-of-origin or histology. Drawing from ideas in supervised text classification, we developed survClust, an outcome-weighted clustering algorithm for integr...

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Literature Corpus work: 2efa9626-95c0-5800-9f9f-2b9f1eb2a2f1
DOI: 10.1101/2020.05.11.084798

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