|
Activity Number:
|
342
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Tuesday, August 8, 2006 : 2:00 PM to 3:50 PM
|
|
Sponsor:
|
Biometrics Section
|
| Abstract - #305535 |
|
Title:
|
Detecting Differential Expressions in GeneChip Microarray Studies: a Quantile Approach
|
|
Author(s):
|
Huixia Wang*+
|
|
Companies:
|
University of Illinois at Urbana-Champaign
|
|
Address:
|
101 Illini Hall, Champaign, IL, 61820,
|
|
Keywords:
|
gene expression ; quantile regression ; microarray data ; random effect ; rank score test
|
|
Abstract:
|
We consider testing for differentially expressed genes in GeneChip studies by modeling the quantiles of gene expression through probe-level measurements. By developing a robust rank-score test for linear quantile models with a random effect, we propose a reliable test for detecting differences in certain quantiles of the intensity distributions. By using a genome-wide adjustment to the test statistic to account for within-array correlation, we demonstrate that the proposed rank-score test is highly effective, even when the number of arrays is small. Our empirical studies show that detecting differences in the quartiles for the probe-level data is a valuable complement to the usual mixed-model analysis based on Gaussian likelihood. The methodology development in this paper is a first attempt at developing inferential tools for quantile regression in mixed models.
|
- 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 2006 program |
