Ugis Sarkans

Minimum information about a microarray experiment (MIAME)-toward standards for microarray data.

Microarray analysis has become a widely used tool for the generation of gene expression data on a genomic scale. Although many significant results have been derived from microarray studies, one limitation has been the lack of standards for presenting and exchanging such data. Here we present a proposal, the Minimum Information About a Microarray Experiment (MIAME), that describes the minimum information required to ensure that microarray data can be easily interpreted and that results derived from its analysis can be independently verified. The ultimate goal of this work is to establish a standard for recording and reporting microarray-based gene expression data, which will in turn facilitate the establishment of databases and public repositories and enable the development of data analysis tools. With respect to MIAME, we concentrate on defining the content and structure of the necessary information rather than the technical format for capturing it.

ArrayExpress—a public repository for microarray gene expression data at the EBI

ArrayExpress is a public repository for microarray data that supports the MIAME (Minimum Informa-tion About a Microarray Experiment) requirements and stores well-annotated raw and normalized data. As of November 2004, ArrayExpress contains data from ∼12 000 hybridizations covering 35 species. Data can be submitted online or directly from local databases or LIMS in a standard format, and password-protected access to prepublication data is provided for reviewers and authors. The data can be retrieved by accession number or queried by vari-ous parameters such as species, author and array platform. A facility to query experiments by gene and sample properties is provided for a growing subset of curated data that is loaded in to the ArrayExpress data warehouse. Data can be visualized and analysed using Expression Profiler, the integrated data analysis tool. ArrayExpress is available at http://www.ebi.ac.uk/arrayexpress.

ArrayExpress—a public database of microarray experiments and gene expression profiles

ArrayExpress is a public database for high throughput functional genomics data. ArrayExpress consists of two parts—the ArrayExpress Repository, which is a MIAME supportive public archive of microarray data, and the ArrayExpress Data Warehouse, which is a database of gene expression profiles selected from the repository and consistently re-annotated. Archived experiments can be queried by experiment attributes, such as keywords, species, array platform, authors, journals or accession numbers. Gene expression profiles can be queried by gene names and properties, such as Gene Ontology terms and gene expression profiles can be visualized. ArrayExpress is a rapidly growing database, currently it contains data from >50 000 hybridizations and >1 500 000 individual expression profiles. ArrayExpress supports community standards, including MIAME, MAGE-ML and more recently the proposal for a spreadsheet based data exchange format: MAGE-TAB. Availability: .

ArrayExpress update—from an archive of functional genomics experiments to the atlas of gene expression

ArrayExpress http://www.ebi.ac.uk/arrayexpress consists of three components: the ArrayExpress Repository—a public archive of functional genomics experiments and supporting data, the ArrayExpress Warehouse—a database of gene expression profiles and other bio-measurements and the ArrayExpress Atlas—a new summary database and meta-analytical tool of ranked gene expression across multiple experiments and different biological conditions. The Repository contains data from over 6000 experiments comprising approximately 200 000 assays, and the database doubles in size every 15 months. The majority of the data are array based, but other data types are included, most recently—ultra high-throughput sequencing transcriptomics and epigenetic data. The Warehouse and Atlas allow users to query for differentially expressed genes by gene names and properties, experimental conditions and sample properties, or a combination of both. In this update, we describe the ArrayExpress developments over the last two years.

ArrayExpress update—an archive of microarray and high-throughput sequencing-based functional genomics experiments

The ArrayExpress Archive (http://www.ebi.ac.uk/arrayexpress) is one of the three international public repositories of functional genomics data supporting publications. It includes data generated by sequencing or array-based technologies. Data are submitted by users and imported directly from the NCBI Gene Expression Omnibus. The ArrayExpress Archive is closely integrated with the Gene Expression Atlas and the sequence databases at the European Bioinformatics Institute. Advanced queries provided via ontology enabled interfaces include queries based on technology and sample attributes such as disease, cell types and anatomy.

ArrayExpress update—trends in database growth and links to data analysis tools

The ArrayExpress Archive of Functional Genomics Data (http://www.ebi.ac.uk/arrayexpress) is one of three international functional genomics public data repositories, alongside the Gene Expression Omnibus at NCBI and the DDBJ Omics Archive, supporting peer-reviewed publications. It accepts data generated by sequencing or array-based technologies and currently contains data from almost a million assays, from over 30 000 experiments. The proportion of sequencing-based submissions has grown significantly over the last 2 years and has reached, in 2012, 15% of all new data. All data are available from ArrayExpress in MAGE-TAB format, which allows robust linking to data analysis and visualization tools, including Bioconductor and GenomeSpace. Additionally, R objects, for microarray data, and binary alignment format files, for sequencing data, have been generated for a significant proportion of ArrayExpress data.

ArrayExpress update—simplifying data submissions

The ArrayExpress Archive of Functional Genomics Data (http://www.ebi.ac.uk/arrayexpress) is an international functional genomics database at the European Bioinformatics Institute (EMBL-EBI) recommended by most journals as a repository for data supporting peer-reviewed publications. It contains data from over 7000 public sequencing and 42 000 array-based studies comprising over 1.5 million assays in total. The proportion of sequencing-based submissions has grown significantly over the last few years and has doubled in the last 18 months, whilst the rate of microarray submissions is growing slightly. All data in ArrayExpress are available in the MAGE-TAB format, which allows robust linking to data analysis and visualization tools and standardized analysis. The main development over the last two years has been the release of a new data submission tool Annotare, which has reduced the average submission time almost 3-fold. In the near future, Annotare will become the only submission route into ArrayExpress, alongside MAGE-TAB format-based pipelines. ArrayExpress is a stable and highly accessed resource. Our future tasks include automation of data flows and further integration with other EMBL-EBI resources for the representation of multi-omics data.

A simple spreadsheet-based, MIAME-supportive format for microarray data: MAGE-TAB

BackgroundSharing of microarray data within the research community has been greatly facilitated by the development of the disclosure and communication standards MIAME and MAGE-ML by the MGED Society. However, the complexity of the MAGE-ML format has made its use impractical for laboratories lacking dedicated bioinformatics support.ResultsWe propose a simple tab-delimited, spreadsheet-based format, MAGE-TAB, which will become a part of the MAGE microarray data standard and can be used for annotating and communicating microarray data in a MIAME compliant fashion.ConclusionMAGE-TAB will enable laboratories without bioinformatics experience or support to manage, exchange and submit well-annotated microarray data in a standard format using a spreadsheet. The MAGE-TAB format is self-contained, and does not require an understanding of MAGE-ML or XML.

Standards for systems biology

High-throughput technologies are generating large amounts of complex data that have to be stored in databases, communicated to various data analysis tools and interpreted by scientists. Data representation and communication standards are needed to implement these steps efficiently. Here we give a classification of various standards related to systems biology and discuss various aspects of standardization in life sciences in general. Why are some standards more successful than others, what are the prerequisites for a standard to succeed and what are the possible pitfalls?

Expression Profiler: next generation—an online platform for analysis of microarray data

Expression Profiler (EP, http://www.ebi.ac.uk/expressionprofiler) is a web-based platform for microarray gene expression and other functional genomics-related data analysis. The new architecture, Expression Profiler: next generation (EP:NG), modularizes the original design and allows individual analysis-task-related components to be developed by different groups and yet still seamlessly to work together and share the same user interface look and feel. Data analysis components for gene expression data preprocessing, missing value imputation, filtering, clustering methods, visualization, significant gene finding, between group analysis and other statistical components are available from the EBI (European Bioinformatics Institute) web site. The web-based design of Expression Profiler supports data sharing and collaborative analysis in a secure environment. Developed tools are integrated with the microarray gene expression database ArrayExpress and form the exploratory analytical front-end to those data. EP:NG is an open-source project, encouraging broad distribution and further extensions from the scientific community.