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OJBTM
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
SUMMARY
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.