Characterizing functional consequences of DNA copy number alterations in breast and ovarian tumors by spaceMap.

ABSTRACT: We propose a novel conditional graphical model - spaceMap - to construct gene regulatory networks from multiple types of high dimensional omic profiles. A motivating application is to characterize the perturbation of DNA copy number alterations (CNAs) on downstream protein levels in tumors. Through a penalized multivariate regression framework, spaceMap jointly models high dimensional protein levels as responses and high dimensional CNAs as predictors. In this setup, spaceMap infers an undirected network among proteins together with a directed network encoding how CNAs perturb the protein network. spaceMap can be applied to learn other types of regulatory relationships from high dimensional molecular profiles, especially those exhibiting hub structures. Simulation studies show spaceMap has

SUBMITTER: Conley CJ 

PROVIDER: S-EPMC7386198 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature