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: 121
Type: Topic Contributed
Date/Time: Monday, July 30, 2012 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Statistical Science
Abstract - #306586
Title: Two-Criterion: A New Bayesian Differentially Expressed Gene Selection Algorithm
Author(s): Fang Yu*+ and Ming-Hui Chen and Lynn Kuo and John S. Davis
Companies: University of Nebraska Medical Center and University of Connecticut and University of Connecticut and University of Nebraska Medical Center
Address: Department of Biostatistics, Omaha, NE, 68198, United States
Keywords: Bayesian Method ; Microarray ; Sequencing ; Differential Expression

Recently, the Bayesian method becomes more popular for analyzing high dimensional gene expression data as it allows us to borrow information across different genes and provides powerful estimators for evaluating gene expression levels. It is crucial to develop a simple but efficient gene selection algorithm for detecting differentially expressed(DE) genes based on the Bayesian estimators. In this paper, we extend the idea of Chen, Ibrahim, and Chi(2008) to propose a new general gene selection algorithm, namely, the two-criterion, for any Bayesian model on gene expression with microarray or sequencing data. The proposed two-criterion method first evaluates the posterior probability of a gene having different gene expressions between two competitive samples. If the obtained posterior probability is large enough, it declares the gene to be DE. The performance of the proposed method is examined and compared to those of several existing methods via several simulations. A real data set is used to further demonstrate the proposed method.

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.