Hierarchical HotNet: identifying hierarchies of altered subnetworks.

ABSTRACT:

Motivation

The analysis of high-dimensional 'omics data is often informed by the use of biological interaction networks. For example, protein-protein interaction networks have been used to analyze gene expression data, to prioritize germline variants, and to identify somatic driver mutations in cancer. In these and other applications, the underlying computational problem is to identify altered subnetworks containing genes that are both highly altered in an 'omics dataset and are topologically close (e.g. connected) on an interaction network.

Results

We introduce Hierarchical HotNet, an algorithm that finds a hierarchy of altered subnetworks. Hierarchical HotNet assesses the statistical significance of the resulting subnetworks over a range of biological scales and explicitly

SUBMITTER: Reyna MA 

PROVIDER: S-EPMC6129270 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature