JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home

Abstract Details

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 - #304862
Title: Bayesian Nonparametric Variable Selection as an Exploratory Tool for Discovering Differentially Expressed Genes
Author(s): Babak Shahbaba*+ and Wesley Johnson
Companies: University of California at Irvine and University of California at Irvine
Address: 2224 Donald Bren Hall, Irvine, CA, 92697, United States
Keywords: Bayesian Inference ; Gene Expression ; Dirichlet Process Mixtures ; Large-scale Scientific Studies

High-throughput scientific studies involving no clear a'priori hypothesis are common. For example, a large-scale genomic study of a disease may examine thousands of genes without hypothesizing that any specific gene is responsible for the disease. In these studies, the objective is to explore a large number of possible factors (e.g. genes) in order to identify a small number that will be considered in follow-up studies that tend to be more thorough and on smaller scales. For large-scale studies, we propose a nonparametric Bayesian approach based on random partition models. Our model thus divides the set of candidate factors into several subgroups according to their degrees of relevance, or potential effect, in relation to the outcome of interest. The model allows for a latent rank to be assigned to each factor according to the overall potential importance of its group. The posterior expectation or mode of these ranks is used to set up a threshold for selecting such factors. Using simulated data, we demonstrate that our approach could be quite effective in finding relevant genes compared to several alternative methods. We apply our model to two large-scale studies.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2012 program

2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.