Online Program Home
My Program

Abstract Details

Activity Number: 601 - Prior Specifications for Finite Bayesian Mixture Models
Type: Invited
Date/Time: Thursday, August 2, 2018 : 8:30 AM to 10:20 AM
Sponsor: International Society for Bayesian Analysis (ISBA)
Abstract #325452
Title: Heterogeneous Reciprocal Graphical Models
Author(s): Yang Ni* and Peter Müller and Yitan Zhu and Yuan Ji
Companies: UT Austin and University of Texas Austin and NorthShore University HealthSystem and NorthShore Univ. HealthSystem / The University of Chicago
Keywords: Dirichlet-multinomial allocation; hierarchical model; model-based clustering; multiplatform genomic data; thresholding prior

We develop novel hierarchical reciprocal graphical models to infer gene networks from heterogeneous data. In the case of data that can be naturally divided into known groups, we propose to connect graphs by introducing a hierarchical prior across group-specific graphs, including a correlation on edge strengths across graphs. Thresholding priors are applied to induce sparsity of the estimated networks. In the case of unknown groups, we cluster subjects into subpopulations and jointly estimate cluster-specific gene networks, again using similar hierarchical priors across clusters. We illustrate the proposed approach by simulation studies and two applications with multiplatform genomic data for multiple cancers.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2018 program