title: Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt.
abstract: 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.
authors.affiliation: Lawrence Berkeley National Laboratory, Berkeley, CA, USA. steffen@stat.berkeley.edu
authors.forename: Steffen
authors.initials: S
authors.lastname: Durinck
authors.forename: Paul T
authors.initials: PT
authors.lastname: Spellman
authors.forename: Ewan
authors.initials: E
authors.lastname: Birney
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Huber
mesh_terms: D002460:Cell Line; D002874:Chromosome Mapping; D016000:Cluster Analysis; D030541:Databases, Genetic; D023281:Genomics / Q000379:methods*; D006801:Humans; D012333:RNA, Messenger / Q000378:metabolism; D012984:Software
chemical_list: D012333:RNA, Messenger