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Cross-study validation of gene expression investigations is   critical in genomic analysis. We developed an R package and associated   object definitions to merge and visualize multiple gene expression   datasets. Our merging functions use arbitrary character IDs and   generate objects that can efficiently support a variety of joint   analyses. Visualization tools support exploration and cross-study   validation of the data, without requiring normalization across   platforms. Tools include ``integrative correlation'' plots that is,   scatterplots of all pairwise correlations in one study against the   corresponding pairwise correlations of another, both for individual   genes and all genes combined.  Gene-specific plots can be used to   identify genes whose changes are reliably measured across studies.   Visualizations also include scatterplots of gene-specific statistics   quantifying relationships between expression and phenotypes of   interest, using linear, logistic and Cox regression.

MergeMaid: R Tools for Merging and Cross-Study Validation of Gene Expression Data