Using the ratio of means as the effect size measure in combining results of microarray experiments |
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Authors: | Pingzhao Hu Celia MT Greenwood Joseph Beyene |
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Affiliation: | (1) The Centre for Applied Genomics, The Hospital for Sick Children, 15-706 TMDT, 101 College Street, Toronto, ON, M5G 1L7, Canada;(2) Dalla Lana School of Public Health, University of Toronto, Health Sciences Building, 155 College St, Toronto, ON, M5T 3M7, Canada;(3) Child Health Evaluative Sciences, The Hospital for Sick Children Research Institute, 555 University Ave, Toronto, ON, M5G 1X8, Canada |
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Abstract: | Background Development of efficient analytic methodologies for combining microarray results is a major challenge in gene expression analysis. The widely used effect size models are thought to provide an efficient modeling framework for this purpose, where the measures of association for each study and each gene are combined, weighted by the standard errors. A significant disadvantage of this strategy is that the quality of different data sets may be highly variable, but this information is usually neglected during the integration. Moreover, it is widely known that the estimated standard deviations are probably unstable in the commonly used effect size measures (such as standardized mean difference) when sample sizes in each group are small. |
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