Tanya Barrett

NCBI GEO: archive for functional genomics data sets—update

The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research community. The resource supports archiving of raw data, processed data and metadata which are indexed, cross-linked and searchable. All data are freely available for download in a variety of formats. GEO also provides several web-based tools and strategies to assist users to query, analyse and visualize data. This article reports current status and recent database developments, including the release of GEO2R, an R-based web application that helps users analyse GEO data.

NCBI GEO: mining tens of millions of expression profiles—database and tools update

The Gene Expression Omnibus (GEO) repository at the National Center for Biotechnology Information (NCBI) archives and freely disseminates microarray and other forms of high-throughput data generated by the scientific community. The database has a minimum information about a microarray experiment (MIAME)-compliant infrastructure that captures fully annotated raw and processed data. Several data deposit options and formats are supported, including web forms, spreadsheets, XML and Simple Omnibus Format in Text (SOFT). In addition to data storage, a collection of user-friendly web-based interfaces and applications are available to help users effectively explore, visualize and download the thousands of experiments and tens of millions of gene expression patterns stored in GEO. This paper provides a summary of the GEO database structure and user facilities, and describes recent enhancements to database design, performance, submission format options, data query and retrieval utilities. GEO is accessible at

NCBI GEO: archive for functional genomics data sets—10 years on

A decade ago, the Gene Expression Omnibus (GEO) database was established at the National Center for Biotechnology Information (NCBI). The original objective of GEO was to serve as a public repository for high-throughput gene expression data generated mostly by microarray technology. However, the research community quickly applied microarrays to non-gene-expression studies, including examination of genome copy number variation and genome-wide profiling of DNA-binding proteins. Because the GEO database was designed with a flexible structure, it was possible to quickly adapt the repository to store these data types. More recently, as the microarray community switches to next-generation sequencing technologies, GEO has again adapted to host these data sets. Today, GEO stores over 20 000 microarray- and sequence-based functional genomics studies, and continues to handle the majority of direct high-throughput data submissions from the research community. Multiple mechanisms are provided to help users effectively search, browse, download and visualize the data at the level of individual genes or entire studies. This paper describes recent database enhancements, including new search and data representation tools, as well as a brief review of how the community uses GEO data. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

NCBI GEO: mining millions of expression profiles—database and tools

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest fully public repository for high-throughput molecular abundance data, primarily gene expression data. The database has a flexible and open design that allows the submission, storage and retrieval of many data types. These data include microarray-based experiments measuring the abundance of mRNA, genomic DNA and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. GEO currently holds over 30 000 submissions representing approximately half a billion individual molecular abundance measurements, for over 100 organisms. Here, we describe recent database developments that facilitate effective mining and visualization of these data. Features are provided to examine data from both experiment- and gene-centric perspectives using user-friendly Web-based interfaces accessible to those without computational or microarray-related analytical expertise. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

NCBI GEO: archive for high-throughput functional genomic data

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest public repository for high-throughput gene expression data. Additionally, GEO hosts other categories of high-throughput functional genomic data, including those that examine genome copy number variations, chromatin structure, methylation status and transcription factor binding. These data are generated by the research community using high-throughput technologies like microarrays and, more recently, next-generation sequencing. The database has a flexible infrastructure that can capture fully annotated raw and processed data, enabling compliance with major community-derived scientific reporting standards such as ‘Minimum Information About a Microarray Experiment’ (MIAME). In addition to serving as a centralized data storage hub, GEO offers many tools and features that allow users to effectively explore, analyze and download expression data from both gene-centric and experiment-centric perspectives. This article summarizes the GEO repository structure, content and operating procedures, as well as recently introduced data mining features. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

Gene expression omnibus: microarray data storage, submission, retrieval, and analysis.

The Gene Expression Omnibus (GEO) repository at the National Center for Biotechnology Information 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 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 1500 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 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/.

Application of cDNA microarrays to examine gene expression differences in schizophrenia

Using cDNA microarrays we have investigated gene expression patterns in brain regions of patients with schizophrenia. A cDNA neuroarray, comprised of genes related to brain function, was used to screen pools of samples from the cerebellum and prefrontal cortex from a matched set of subjects, and middle temporal gyrus, from a separate subject cohort. Samples of cerebellum and prefrontal cortex from neuroleptic naive patients were also included. Genes that passed a 3% reproducibility criterion for differential expression in independent experiments included 21 genes for drug-treated patients and 5 genes for drug-naive patients. Of these 26 genes, 10 genes were increased and 16 were decreased. Many of the differentially expressed genes were related to synaptic signaling and proteolytic functions. A smaller number of these genes were also differentially expressed in the middle temporal gyrus. The five genes that were differentially expressed in two brain regions from separate cohorts are: tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, eta polypeptide; sialyltransferase; proteasome subunit, alpha type 1; ubiquitin carboxyl-terminal esterase L1; and solute carrier family 10, member 1. Identification of patterns of changes in gene expression may lead to a better understanding of the pathophysiology of schizophrenia disorders.

BioProject and BioSample databases at NCBI: facilitating capture and organization of metadata

As the volume and complexity of data sets archived at NCBI grow rapidly, so does the need to gather and organize the associated metadata. Although metadata has been collected for some archival databases, previously, there was no centralized approach at NCBI for collecting this information and using it across databases. The BioProject database was recently established to facilitate organization and classification of project data submitted to NCBI, EBI and DDBJ databases. It captures descriptive information about research projects that result in high volume submissions to archival databases, ties together related data across multiple archives and serves as a central portal by which to inform users of data availability. Concomitantly, the BioSample database is being developed to capture descriptive information about the biological samples investigated in projects. BioProject and BioSample records link to corresponding data stored in archival repositories. Submissions are supported by a web-based Submission Portal that guides users through a series of forms for input of rich metadata describing their projects and samples. Together, these databases offer improved ways for users to query, locate, integrate and interpret the masses of data held in NCBIs archival repositories. The BioProject and BioSample databases are available at http://www.ncbi.nlm.nih.gov/bioproject and http://www.ncbi.nlm.nih.gov/biosample, respectively.

NCBI GEO standards and services for microarray data

The Minimum Information About a Microarray Experiment (MIAME) guidelines are a data content document developed by the Microarray Gene Expression Data (MGED) Society that outlines the information that should be provided when describing a microarray experiment1. Many journals and funding agencies have adopted the guidelines, with the aim of facilitating access to the elements of a study that would enable independent evaluation of results. However, the MIAME requirements have been criticized recently2, 3. The criticism stems, in part, from different interpretations of the level of detail required to adequately report a microarray experiment, and debates as to whether there is a genuine benefit to making microarray data public. The Gene Expression Omnibus (GEO) database at the National Center for Biotechnology Information (NCBI)4 and ArrayExpress at the European Bioinformatics Institute (EBI)5 are the two major public databases of microarray data. Although they have different designs, both databases support capture of all data elements defined by MIAME. Figure 1 presents a timeline of major landmarks in the evolution of the GEO database, together with concomitant growth in submissions. GEO was launched in 2000, more than a year before the MIAME guidelines were proposed. Because there was not yet a consensus on reporting standards for microarray data, or even an obligation to make microarray data public, GEO initially allowed a minimal level of experimental detail to be supplied. Over the ensuing years we continually monitored the needs and requests of end-users, and gauged the level of effort submitters were realistically willing to invest in making their data public. We responded with incremental improvements to database design and curation standards, and we developed easy-to-generate batch deposit formats that significantly reduced the burden of submission and allowed contributors to focus on the content submitted rather than the mechanism of submission. Figure 1 Timeline of GEO growth and major landmarks in evolution of GEO database, and a screenshot of GEO tools which allow users to query, analyze, and visualize the data in GEO. In June 2005, we released major database revisions that included specific provisions for all MIAME data elements. In 2006, mechanisms for provision of raw data were further streamlined, and several MIAME elements that were previously optional became mandatory. Yet, even with these advances, it is still possible for a submitter to supply data that do not strictly adhere to the MIAME requirements. The difficulty lies in the fact that MIAME is a subjective set of guidelines where the level of detail to report is open to interpretation and, thus, cannot be unequivocally validated or enforced by computational means. All data submitted to GEO are syntactically validated for correct document structure, organization, and provision of basic elements. Next, each submission is inspected by curators for content integrity. GEO curators employ a pragmatic approach; we aim to ensure that sufficient information has been supplied to allow general interpretation of the experiment. Although encouraged, we have been less dogmatic with regards to provision of all-inclusive experimental protocols that would possibly permit practical replication of the entire experiment. Our reasoning is that provision of granulated experimental details adds a significant burden on the submitter, for (arguably) minimal real benefit for most end-users who are usually less concerned with this level of detail. When content or format problems are identified, curators work with the submitter until the issue is resolved. Submissions lacking critical descriptive elements necessary for overall experiment interpretation are not approved for public release. However, given the large diversity of biological themes, technologies, and statistical transformations applied to microarray data, it is impractical for curators to decisively determine the accuracy and validity of the data, or to assess if all relevant information has been supplied. This is where the role of reviewers and editors becomes important. The GEO database has had mechanisms for anonymous reviewer access to prepublication data since 2003. Over the last several years, authors have occasionally requested curator comment regarding the level of MIAME-compliance of their submissions, and we have been happy to offer feedback on areas that could be improved. GEO staff are similarly available to support reviewers and editors by providing tailored inspections of MIAME compliance of specific submissions upon request of the journal, as ArrayExpress is proposing to do6. If a reviewer determines that insufficient information has been supplied, the GEO database is designed such that authors can quickly respond by updating their records accordingly. It has been challenging to find the optimal balance between submitter effort and the appropriate level of metadata detail to request, all within a rapidly evolving technological and social environment7. However, the relative simplicity of the GEO database structure, together with common-sense curation policies that focus on gathering germane MIAME elements, have made it possible for us to develop an extensive suite of utilities that make the volumes of complex data archived at GEO accessible and easy to use by the research community at large8. Ultimately, the value of a database is reflected by how it is used by the community it serves. In the past month, GEO received approximately one million query hits, and over 200,000 file transfer downloads amounting to over 2.5 terabytes of compressed data. Furthermore, it is clear that researchers are applying these data to their own studies, as evidenced by over 100 recent publications citing data found in GEO to support or otherwise complement their own studies9. We view this as testament that the effort involved in making expression data public via GEO is fully justified.

Region-specific transcriptional response to chronic nicotine in rat brain

Even though nicotine has been shown to modulate mRNA expression of a variety of genes, a comprehensive high-throughput study of the effects of nicotine on the tissue-specific gene expression profiles has been lacking in the literature. In this study, cDNA microarrays containing 1117 genes and ESTs were used to assess the transcriptional response to chronic nicotine treatment in rat, based on four brain regions, i.e. prefrontal cortex (PFC), nucleus accumbens (NAs), ventral tegmental area (VTA), and amygdala (AMYG). On the basis of a non-parametric resampling method, an index (called jackknifed reliability index, JRI) was proposed, and employed to determine the inherent measurement error across multiple arrays used in this study. Upon removal of the outliers, the mean correlation coefficient between duplicate measurements increased to 0.978+/-0.0035 from 0.941+/-0.045. Results from principal component analysis and pairwise correlations suggested that brain regions studied were highly similar in terms of their absolute expression levels, but exhibited divergent transcriptional responses to chronic nicotine administration. For example, PFC and NAs were significantly more similar to each other (r=0.7; P<10(-14)) than to either VTA or AMYG. Furthermore, we confirmed our microarray results for two representative genes, i.e. the weak inward rectifier K(+) channel (TWIK-1), and phosphate and tensin homolog (PTEN) by using real-time quantitative RT-PCR technique. Finally, a number of genes, involved in MAPK, phosphatidylinositol, and EGFR signaling pathways, were identified and proposed as possible targets in response to nicotine administration.