JSM 2005 Online Program

Abstract #302311

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. 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, 2005); 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.

The Program has labeled the meeting rooms with "letters" preceding the name of the room, designating in which facility the room is located:

Minneapolis Convention Center = “MCC” Hilton Minneapolis Hotel = “H” Hyatt Regency Minneapolis = “HY”

Back to main JSM 2005 Program page

Legend:

= Applied Session,

= Theme Session,

= Presenter

Activity Number:	87
Type:	Invited
Date/Time:	Monday, August 8, 2005 : 8:30 AM to 10:20 AM
Sponsor:	IMS
Abstract - #302311
Title:	A Two-way, Semilinear Model for Normalization and Analysis of Microarray Data
Author(s):	Jian Huang*+ and Cun-Hui Zhang
Companies:	The University of Iowa and Rutgers University
Address:	Department of Statistics and Act Sci, 241 SH, Iowa City, 52242, U.S.
Keywords:	differentially expressed genes ; microarray ; high-dimensional data ; semiparametric regression ; spline ; analysis of variance
Abstract:	A basic question in analyzing Cdna microarray data is normalization---the purpose of which is to remove systematic bias in the observed expression values by establishing a normalization curve across the whole dynamic range. A proper normalization procedure ensures the normalized intensity ratios provide meaningful measures of relative expression levels. In this paper, we propose a two-way, semi-linear model (TW-SLM) for normalization and analysis of microarray data. This method does not make the usual assumptions underlying some of the existing methods. The TW-SLM also naturally incorporates uncertainty due to normalization into significance analysis of microarrays. We use a semiparametric approach based on polynomial splines to estimate the normalization curves and the normalized expression values. We study the theoretical properties of the proposed estimator in the TW-SLM, including the finite sample distributional properties of the estimated gene effects and the rate of convergence of the estimated normalization curves when the number of genes under study is large. We also conduct simulation studies to evaluate the TW-SLM 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 2005 program