Mapping Identifiers for the Integration of Genomic Datasets with the R/Bioconductor package biomaRt

Genomic experiments yield multiple complementary views of biological systems, among them DNA sequence, copy number variation, and mRNA and protein abundance, and making sense of these requires integrated bioinformatic analysis. Public databases such as Ensembl provide the relationships and mappings between the relevant probe and target molecules, but those relationships can be biologically complex and the database content is dynamic. This protocol demonstrates how to use the computational environment R, together with BioMart web services accessed through the biomaRt package, to integrate and jointly analyze experimental datasets by supplying the necessary molecule mappings.

The protocol also discusses typical problems encountered when making gene-to-transcript-to-protein mappings, offering practical guidance for these common integration challenges. By combining R with BioMart web services, the approach provides a flexible, programmable, and reproducible basis for state-of-the-art bioinformatic data integration, which mattered for researchers needing to reliably link and jointly analyze heterogeneous genomic measurements across evolving public databases.