Meta-analysis of gene expression microarrays with missing replicates
Fan Shi, Gad Abraham, Christopher Leckie, Izhak Haviv, Adam Kowalczyk
BMC Bioinformatics | BMC | Published : 2011
BACKGROUND: Many different microarray experiments are publicly available today. It is natural to ask whether different experiments for the same phenotypic conditions can be combined using meta-analysis, in order to increase the overall sample size. However, some genes are not measured in all experiments, hence they cannot be included or their statistical significance cannot be appropriately estimated in traditional meta-analysis. Nonetheless, these genes, which we refer to as incomplete genes, may also be informative and useful. RESULTS: We propose a meta-analysis framework, called "Incomplete Gene Meta-analysis", which can include incomplete genes by imputing the significance of missing rep..View full abstract
This work was supported by the Australian Research Council, and by the NICTA Victorian Research Laboratory. NICTA is funded by the Australian Government as represented by the Department of Broadband, Communications and the Digital Economy and the Australian Research Council through the ICT Center of Excellence program.