MergeMaid: R Tools for Merging and Cross-Study Validation of Gene Expression Data
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.
Year of publication: |
2004
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Authors: | Leslie, Cope ; Xiaogang, Zhong ; Elizabeth, Garrett ; Giovanni, Parmigiani |
Published in: |
Statistical Applications in Genetics and Molecular Biology. - De Gruyter, ISSN 1544-6115. - Vol. 3.2004, 1, p. 1-15
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Publisher: |
De Gruyter |
Saved in:
Saved in favorites
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