A Novel Method for Cancer Subtyping and Risk Prediction Using Consensus Factor Analysis.

ABSTRACT: Cancer is an umbrella term that includes a range of disorders, from those that are fast-growing and lethal to indolent lesions with low or delayed potential for progression to death. One critical unmet challenge is that molecular disease subtypes characterized by relevant clinical differences, such as survival, are difficult to differentiate. With the advancement of multi-omics technologies, subtyping methods have shifted toward data integration in order to differentiate among subtypes from a holistic perspective that takes into consideration phenomena at multiple levels. However, these integrative methods are still limited by their statistical assumption and their sensitivity to noise. In addition, they are unable to predict the risk scores of patients using multi-omics data. Here, we pre

SUBMITTER: Tran D 

PROVIDER: S-EPMC7344292 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature