JSM 2004 - Toronto

Abstract #300124

This is the preliminary program for the 2004 Joint Statistical Meetings in Toronto, Canada. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2004); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

To View the Program:
You may choose to view all activities of the program or just parts of it at any one time. All activities are arranged by date and time.

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.

Back to main JSM 2004 Program page
Activity Number: 8
Type: Invited
Date/Time: Sunday, August 8, 2004 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #300124
Title: Some Recent Developments for Massive Multiple Comparisons and Clustering of Microarray Gene Expression Data
Author(s): Kim-Anh Do*+
Companies: University of Texas M.D. Anderson Cancer Center
Address: Dept. of Biostatistics, Houston, TX, 77030-4009,
Keywords: microarray ; gene expression
Abstract:

We discuss two new methodology/software developments for the analysis of microarray gene expression: (1) Model-based inference is proposed for differential gene expression, using a nonparametric Bayesian probability model for the distribution of gene intensities under different conditions. The probability model is a variation of traditional Dirichlet process (DP) mixture models. We illustrate the proposed method in a simulation study and a microarray experiment in colon cancer versus normal tissue. We will discuss the ease of making joint inference about a subgroup of genes being differentially expressed and of estimating the total number of significantly expressing genes. Further, the control of false positive rates can be automatically incorporated into this approach. (2) ''Geneshaving'' and the related program GeneClust (developed at M.D. Anderson Cancer Center), can be used for either supervised or unsupervised clustering of microarray gene expression data. The method is discussed and applied to the analysis of some well-known datasets: the colon data of Alon et al. (2000), the leukemia data of Golub, et al. (2000), and the NCI60 data.

  • 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 2004 program

JSM 2004 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.
Revised March 2004