Abstract

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.

Submitted: February 4, 2004 · Accepted: September 23, 2004 · Published: October 31, 2004

Recommended Citation

Cope, Leslie; Zhong, Xiaogang; Garrett, Elizabeth; and Parmigiani, Giovanni (2004) "MergeMaid: R Tools for Merging and Cross-Study Validation of Gene Expression Data," Statistical Applications in Genetics and Molecular Biology: Vol. 3 : Iss. 1, Article 29.
DOI: 10.2202/1544-6115.1046
Available at: http://www.bepress.com/sagmb/vol3/iss1/art29