Gene Expression Omnibus ( GEO ) : Microarray data storage , submission , retrieval , and analysis

The Gene Expression Omnibus (GEO) repository at the National Center for Biotechnology Information (NCBI) archives and freely distributes high-throughput molecular abundance data, predominantly gene expression data generated by DNA microarray technology. The database has a flexible design that can handle diverse styles of both unprocessed and processed data in a MIAME(Minimum Information About a Microarray Experiment) supportive infrastructure that promotes fully annotated submissions. GEO currently stores about a billion individual gene expression measurements, derived from over 100 organisms, submitted by over 1,500 laboratories, addressing a wide range of biological phenomena. To maximize the utility of these data, several user-friendly Web-based interfaces and applications have been implemented that enable effective exploration, query, and visualization of these data, at the level of individual genes or entire studies. This chapter describes how the data are stored, submission procedures, and mechanisms for data retrieval and query. GEO is publicly accessible at http://www.ncbi.nlm.nih.gov/projects/geo/. THE PURPOSE AND SCOPE OF GEO The post-genomic era has led to a multitude of high-throughput methodologies that generate massive volumes of gene expression data. The GEO repository was established by NCBI in 2000 to house and distribute these data to the public with no restrictions or login requirements (for more information, please read the GEO Data Disclaimer1). The primary role of GEO is data archiving, functioning as a hub for data deposit and retrieval (Edgar et al., 2002;Barrett et al, 2005). GEO is currently the largest, fully public gene expression resource. At the time of writing, the database holds over 50,000 samples, comprising approximately a billion individual expression measurements, 13 million gene expression profiles, for over 100 organisms, submitted by almost 1,500 laboratories. These data address a very broad diversity of biological themes including disease, development, evolution, metabolics, toxicology, immunity, ecology, transgenesis, and so on. Most data are provided by the research community in compliance with grant or journal provisos that require microarray data to be made available in a public repository, the objective being to facilitate independent evaluation of results, reanalysis, and full access to all parts of the study (Ball et al., 2004). Correspondence to: Ron Edgar. edgar@ncbi.nlm.nih.gov, NIH/NLM/NCBI, 45 Center Drive, MSC 6510, Building 45, Room AS25A, Bethesda, MD, 20892-6510, Ph: (301) 435-3449, Fax: (301) 480-0109 barrett@ncbi.nlm.nih.gov, NIH/NLM/NCBI, 45 Center Drive, MSC 6510, Building 45, Room AS21, Bethesda, MD, 20892-6510, Ph: (301) 402-4057, Fax: (301) 480-0109 This chapter is an official contribution of the National Institutes of Health; not subject to copyright in the United States. 1http://www.ncbi.nlm.nih.gov/projects/geo/info/disclaimer.html NIH Public Access Author Manuscript Methods Enzymol. Author manuscript; available in PMC 2006 October 23. Published in final edited form as: Methods Enzymol. 2006 ; 411: 352–369. N IH PA Athor M anscript N IH PA Athor M anscript N IH PA Athor M anscript Data types currently stored include, but are not limited to, cDNA and oligonucleotide microarrays that examine gene expression, serial analysis of gene expression (SAGE), massively parallel signature sequencing (MPSS), array comparative genomic hybridization, chromatin-immunoprecipitation on arrays (ChIP-chip) studies, and peptide profiling techniques such as tandem mass spectrometry (MS/MS). In keeping with the theme of the book, this chapter will focus on gene expression data generated by DNA microarrays. Although primarily a data storage and retrieval facility, it was clear early on that the resource must also enable effective searching and data mining as means to identify entries of interest. Consequently, several user-friendly Web-based query tools have been developed to assist even those unfamiliar with microarray technology to effectively explore and analyze GEO data. However, it is important to realize that GEO is not intended to be used as a Laboratory Information Management System (LIMS), or a pre-/first-analysis environment, since data submitted to GEO are generally processed data that form the basis for discussion in accompanying manuscripts. This chapter explains the database design for storage of microarray information, how to submit data, and how to effectively retrieve and examine information in the GEO database.