©1996-2009 All Rights Reserved. Online Journal of Bioinformatics
Online Journal of Bioinformatics©
Volume 10 (1):67-73, 2009
Multiple contrast test for detecting monotonic dose-response relationship and FDR-adjusted confidence intervals for selected parameters in a microarray Setting
Lin D1, Shkedy Z1, Burzykowski T1, Yekutieli D2, De Bondt A3, Göhlmann WHH3, Talloen W3, Bijnens L3
1- Hasselt University, I-BioStat, Universitaire Campus, Building D, B 3590 Diepenbeek, Belgium 2- Department of Statistics and Operation Research, School of Mathematical Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv, 69978, Israel, 3- J&JPRD - Biometrics and Clinical Informatics, Beerse, Belgium
Lin D, Shkedy Z, Burzykowski T, Yekutieli D, De Bondt A, Goehlmann H, Talloen W, Bijnens L., Multiple contrast test for detecting monotonic dose-response relationship and FDR-adjusted confidence intervals for selected parameters in a microarray Setting, Online J Bioinformatics, 10(1):67-73,2009. Dose-response microarray experiments consist of monitoring expression levels of thousands of genes with respect to increasing doses of the compound treatment under investigation. In this paper we discuss a microarray dose-response experiment in which gene expression data are available for a control and several treatment doses. That fact that the gene expression increases/decreases with the increasing doses constitute the active dose-response relationship in this setting. We aim at comparing the (relative) mean difference in gene expression between higher doses and the control. Especially, we direct this test by using Marcus' multiple contrasts to obtain the isotonic means, as proposed byBretz (2006). Moreover, we show an application of the multiple ratio tests, discussed by Dilba et al. (2005), to the data. Furthermore, we construct simultaneous confidence intervals for a selected subset of genes following the ratio tests, Benjamini and Yekutieli (2005) addressed the issue of multiplicity due to effect of testing and selecting the parameters of interest. The Benjamini and Hochberg (1995) procedure for controlling FDR is applied to address the multiple testing issue. To construct confidence intervals for selected parameters, the False Discovery Rate (FDR) adjusted procedure (Benjamini and Yekutieli, 2005) is applied. The case study used for illustration is a dose-response microarray experiment with 12 samples (three arrays at each of four dose levels) and arrays consisting of 16998 genes.
Keywords: Microarray; Dose Response; Ratio test; False Discovery Rate (FDR) Adjusted Multiple Confidence Intervals (CI); Selected Parameters.