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Classical and Bayesian random-effects meta-analysis models with sample quality weights in gene expression studies
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Random-effects (RE) models are commonly applied to account for heterogeneity in effect sizes in gene expression meta-analysis. The degree of heterogeneity may differ due to inconsistencies in sample quality. High heterogeneity can arise in meta-analyses containing poor quality samples.
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