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Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt


Genomic experiments produce multiple views of biological systems, among them are DNA sequence and copy number variation, and mRNA and protein abundance. Understanding these systems needs integrated bioinformatic analysis. Public databases such as Ensembl provide relationships and mappings between the relevant sets of probe and target molecules. However, the relationships can be biologically complex and the content of the databases is dynamic. We demonstrate how to use the computational environment R to integrate and jointly analyze experimental datasets, employing BioMart web services to provide the molecule mappings. We also discuss typical problems that are encountered in making gene-to-transcript–to-protein mappings. The approach provides a flexible, programmable and reproducible basis for state-of-the-art bioinformatic data integration.

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Figure 1: Principal component analysis using the mRNA profiles of the 200 most variable probesets.
Figure 2: The CGH log-ratios of chromosome I for three cell lines (MCF10A, BT549 and BT483).
Figure 3: Expression data of probes mapping to chromosome 1 for the two cell lines BT483 and BT549.
Figure 4
Figure 5: Heatmap showing a hierarchical clustering of the proteins (down right-hand side) and samples (along the bottom) based on the protein expression measurements.
Figure 6: Expression profiles of AURKA over the cell lines (along the x-axis) for mRNA (orange) and protein (green) levels.
Figure 7: Scatterplots of protein expression levels versus mRNA expression levels in four cell lines.


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We thank Arek Kasprzyk and Rhoda Kinsella for insightful discussions.

This work was partially funded by the U24 CA126551 grant.

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Correspondence to Steffen Durinck.

Supplementary information

Supplementary Data 1

Zip archive containing the raw data of the Neve et al. study on a panel of 51 breast cell lines. It consists of Affymetrix CEL files of gene expression measurements deposited in ArrayExpress as experiment E-TABM-157, and Array CGH and protein quantification data which are available from (ZIP 168067 kb)

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Durinck, S., Spellman, P., Birney, E. et al. Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt. Nat Protoc 4, 1184–1191 (2009).

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