Clustering multilayer omics data using MuNCut.

ABSTRACT:

Background

Omics profiling is now a routine component of biomedical studies. In the analysis of omics data, clustering is an essential step and serves multiple purposes including for example revealing the unknown functionalities of omics units, assisting dimension reduction in outcome model building, and others. In the most recent omics studies, a prominent trend is to conduct multilayer profiling, which collects multiple types of genetic, genomic, epigenetic and other measurements on the same subjects. In the literature, clustering methods tailored to multilayer omics data are still limited. Directly applying the existing clustering methods to multilayer omics data and clustering each layer first and then combing across layers are both "suboptimal" in that they do not accommodate

SUBMITTER: Teran Hidalgo SJ 

PROVIDER: S-EPMC5991460 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature