VWCluster: Vector-valued optimal transport for network based clustering using multi-omics data in breast cancer.

ABSTRACT: In this paper, we present a network-based clustering method, called vector Wasserstein clustering (vWCluster), based on the vector-valued Wasserstein distance derived from optimal mass transport (OMT) theory. This approach allows for the natural integration of multi-layer representations of data in a given network from which one derives clusters via a hierarchical clustering approach. In this study, we applied the methodology to multi-omics data from the two largest breast cancer studies. The resultant clusters showed significantly different survival rates in Kaplan-Meier analysis in both datasets. CIBERSORT scores were compared among the identified clusters. Out of the 22 CIBERSORT immune cell types, 9 were commonly significantly different in both datasets, suggesting the difference of tu

SUBMITTER: Zhu J 

PROVIDER: S-EPMC8920287 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature