A Unified Mixed Effects Model for Gene Set Analysis of Time Course Microarray Experiments
Methods for gene set analysis test for coordinated changes of a group of genes involved in the same biological process or molecular pathway. Higher statistical power is gained for gene set analysis by combining weak signals from a number of individual genes in each group. Although many gene set analysis methods have been proposed for microarray experiments with two groups, few can be applied to time course experiments. We propose a unified statistical model for analyzing time course experiments at the gene set level using random coefficient models, which fall into the more general class of mixed effects models. These models include a systematic component that models the mean trajectory for the group of genes, and a random component (the random coefficients) that models how each gene's trajectory varies about the mean trajectory.
Year of publication: |
2009
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Authors: | Lily, Wang ; Xi, Chen ; D, Wolfinger Russell ; L, Franklin Jeffrey ; J, Coffey Robert ; Bing, Zhang |
Published in: |
Statistical Applications in Genetics and Molecular Biology. - De Gruyter, ISSN 1544-6115. - Vol. 8.2009, 1, p. 1-18
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Publisher: |
De Gruyter |
Saved in:
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