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RECOMB
2009
Springer

A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series

10 years 2 months ago
A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series
Abstract. Understanding the regulatory mechanisms that are responsible for an organism's response to environmental changes is an important question in molecular biology. A first and important step towards this goal is to detect genes whose expression levels are affected by altered external conditions. A range of methods to test for differential gene expression, both in static as well as in time-course experiments, have been proposed. While these tests answer the question whether a gene is differentially expressed, they do not explicitly address the question when a gene is differentially expressed, although this information may provide insights into the course and causal structure of regulatory programs. In this article, we propose a two-sample test for identifying intervals of differential gene expression in microarray time series. Our approach is based on Gaussian process regression, can deal with arbitrary numbers of replicates and is robust with respect to outliers. We apply ou...
Oliver Stegle, Katherine J. Denby, David L. Wild,
Added 23 Nov 2009
Updated 23 Nov 2009
Type Conference
Year 2009
Where RECOMB
Authors Oliver Stegle, Katherine J. Denby, David L. Wild, Zoubin Ghahramani, Karsten M. Borgwardt
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