Modeling sample variables with an Experimental Factor Ontology

Motivation: Describing biological sample variables with ontologies is complex due to the cross-domain nature of experiments. Ontologies provide annotation solutions; however, for cross-domain investigations, multiple ontologies are needed to represent the data. These are subject to rapid change, are often not interoperable and present complexities that are a barrier to biological resource users

Importing ArrayExpress datasets into R/Bioconductor

Summary:ArrayExpress is one of the largest public repositories of microarray datasets. R/Bioconductor provides a comprehensive suite of microarray analysis and integrative bioinformatics software. However, easy ways for importing datasets from ArrayExpress into R/Bioconductor have been lacking. Here, we present such a tool that is suitable for both interactive and automated use

Low level genome mistranslations deregulate the transcriptome and translatome and generate proteotoxic stress in yeast

Organisms use highly accurate molecular processes to transcribe their genes and a variety of mRNA quality control and ribosome proofreading mechanisms to maintain intact the fidelity of genetic information flow. Despite this, low level gene translational errors induced by mutations and environmental factors cause neurodegeneration and premature death in mice and mitochondrial disorders in humans. Paradoxically, such errors can generate advantageous phenotypic diversity in fungi and bacteria through poorly understood molecular processes.publishe

Pomelo II: finding differentially expressed genes

Pomelo II (http://pomelo2.bioinfo.cnio.es) is an open-source, web-based, freely available tool for the analysis of gene (and protein) expression and tissue array data. Pomelo II implements: permutation-based tests for class comparisons (t-test, ANOVA) and regression; survival analysis using Cox model; contingency table analysis with Fisher's exact test; linear models (of which t-test and ANOVA are especial cases) that allow additional covariates for complex experimental designs and use empirical Bayes moderated statistics. Permutation-based and Cox model analysis use parallel computing, which permits taking advantage of multicore CPUs and computing clusters. Access to, and further analysis of, additional biological information and annotations (PubMed references, Gene Ontology terms, KEGG and Reactome pathways) are available either for individual genes (from clickable links in tables and figures) or sets of genes. The source code is available, allowing for extending and reusing the software. A comprehensive test suite is also available, and covers both the user interface and the numerical results. The possibility of including additional covariates, parallelization of computation, open-source availability of the code and comprehensive testing suite make Pomelo II a unique tool

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:

4DXpress: a database for cross-species expression pattern comparisons

In the major animal model species like mouse, fish or fly, detailed spatial information on gene expression over time can be acquired through whole mount in situ hybridization experiments. In these species, expression patterns of many genes have been studied and data has been integrated into dedicated model organism databases like ZFIN for zebrafish, MEPD for medaka, BDGP for Drosophila or GXD for mouse. However, a central repository that allows users to query and compare gene expression patterns across different species has not yet been established. Therefore, we have integrated expression patterns for zebrafish, Drosophila, medaka and mouse into a central public repository called 4DXpress (expression database in four dimensions). Users can query anatomy ontology-based expression annotations across species and quickly jump from one gene to the orthologues in other species. Genes are linked to public microarray data in ArrayExpress. We have mapped developmental stages between the species to be able to compare developmental time phases. We store the largest collection of gene expression patterns available to date in an individual resource, reflecting 16 505 annotated genes. 4DXpress will be an invaluable tool for developmental as well as for computational biologists interested in gene regulation and evolution. 4DXpress is available at http://ani.embl.de/4DXpress

VisHiC—hierarchical functional enrichment analysis of microarray data

Measuring gene expression levels with microarrays is one of the key technologies of modern genomics. Clustering of microarray data is an important application, as genes with similar expression profiles may be regulated by common pathways and involved in related functions. Gene Ontology (GO) analysis and visualization allows researchers to study the biological context of discovered clusters and characterize genes with previously unknown functions. We present VisHiC (Visualization of Hierarchical Clustering), a web server for clustering and compact visualization of gene expression data combined with automated function enrichment analysis. The main output of the analysis is a dendrogram and visual heatmap of the expression matrix that highlights biologically relevant clusters based on enriched GO terms, pathways and regulatory motifs. Clusters with most significant enrichments are contracted in the final visualization, while less relevant parts are hidden altogether. Such a dense representation of microarray data gives a quick global overview of thousands of transcripts in many conditions and provides a good starting point for further analysis. VisHiC is freely available at http://biit.cs.ut.ee/vishic

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