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betr | An improved empirical bayes approach to estimating differential gene expression in microarray time-course data


A package to identify differentially expressed genes in microarray time-course data. BETR explicitly uses the time-dependent structure of the data, employing an empirical Bayes procedure to stabilize estimates derived from the small sample sizes typical in microarray experiments. It is applicable to one- or two-color replicated microarray data, and can be used to detect differences between two conditions or changes from baseline in a single condition. BETR outperforms three commonly used techniques in the analysis of time-course data. This advantage is particularly noticeable for genes with a small but sustained differential expression signal. When the magnitude of differential expression is of similar magnitude to background noise, it is difficult to identify by examining each time point in isolation. These patterns of differential expression become easier to identify when the time series structure of the data is taken into account; a small, noisy signal becomes identifiable if it is sustained across several adjoining time points.

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betr specifications

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Bayesian Estimation of Temporal Regulation
Command line interface
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Unix/Linux, Mac OS, Windows
GNU Lesser General Public License version 3.0

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Department of Biostatistics, Harvard School of Public Health, MA, USA

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