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Activity Number: 181
Type: Contributed
Date/Time: Monday, July 30, 2012 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #305835
Title: Differential Patterns of Interaction and Gaussian Graphical Models
Author(s): Masanao Yajima*+ and Donatello Telesca and Yuan Ji and Peter Mueller
Companies: University of California at Los Angeles and University of California at Los Angeles Fielding School of Public Health and Northshore University Healthcare System and The University of Texas at Austin
Address: 3300 Sawtelle Blvd, Los Angeles, CA, 90066, United States
Keywords: DAG ; RJMCMC ; covariance selection models ; differential association

We propose a methodological framework to assess heterogeneous patterns of association amongst components of a random vector expressed as a Gaussian directed acyclic graph. The proposed framework is likely to be useful when primary interest focuses on potential contrasts characterizing the association structure between known subgroups of a given sample. We provide inferential frameworks as well as an efficient computational algorithm to fit such a model and illustrate its validity through a simulation. We apply the model to a Reverse Phase Protein Array data on Acute Myeloid Leukemia patients to show the contrast of association structure between the refractory patients and the relapsed patients.

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