Expression Atlas update—a database of gene and transcript expression from microarray- and sequencing-based functional genomics experiments

By R. Petryszak, Tony Burdett, Benedetto Fiorelli, Nuno A. Fonseca, Mar Gonzàlez-Porta, Emma Hastings, Wolfgang Huber, S. Jupp, M. Keays, Nataliya Kryvych and 11 more. Nucleic Acids Res., 2013

330 citations recorded by the source corpus.

Expression Atlas (http://www.ebi.ac.uk/gxa) is a value-added database providing information about gene, protein and splice variant expression in different cell types, organism parts, developmental stages, diseases and other biological and experimental conditions. The database consists of selected high-quality microarray and RNA-sequencing experiments from ArrayExpress that have been manually curated, annotated with Experimental Factor Ontology terms and processed using standardized microarray and RNA-sequencing analysis methods. The new version of Expression Atlas introduces the concept of ‘baseline’ expression, i.e. gene and splice variant abundance levels in healthy or untreated conditions, such as tissues or cell types. Differential gene expression data benefit from an in-depth curation of experimental intent, resulting in biologically meaningful ‘contrasts’, i.e. instances of differential pairwise comparisons between two sets of biological replicates. Other novel aspects of Expression Atlas are its strict quality control of raw experimental data, up-to-date RNA-sequencing analysis methods, expression data at the level of gene sets, as well as genes and a more powerful search interface designed to maximize the biological value provided to the user.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/220bbf4b673d1c4d1294a7d09f1f0c32e5579a87

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Citations in the corpus

Ensembl 2016 (2015, methodology): “These same APIs are used to build our website and analysis methods and they are available externally for others to use in building their own methods and tools.”
ArrayExpress update—simplifying data submissions (2014, background): “This study also appears in the baseline component of the Expression Atlas at EBI (htttp://www.ebi.ac.uk/gxa/ experiments/E-MTAB-1733), where one can query genes or tissue-specific expression.”
limma powers differential expression analyses for RNA-sequencing and microarray studies (2015, background): “gov/geo/geo2r), the EBI expression atlas (75), Guide (76) and Degust (http://www.”
Benchmark and integration of resources for the estimation of human transcription factor activities (2018, methodology): “Data are available to download from the Expression Atlas (Petryszak et al. 2014) under the accessions E-MTAB-3983, EMTAB-2770, and E-MTAB-2706, respectively.”
WikiPathways: capturing the full diversity of pathway knowledge (2015, methodology): “The goal of this feature is to combine the pathway knowledge from WikiPathways with baseline expression data for 27 different tissues from Expression Atlas (11,12) to study the activity of biological pathways in a specific tissue.”
STITCH 5: augmenting protein–chemical interaction networks with tissue and affinity data (2015, methodology): “In contrast, datasets from the Expression Atlas are transformed into percentiles.”
Distribution of miRNA expression across human tissues (2016, background): “The gene expression atlas (1), hosted at the European Bioinformatics Institute, collects gene expression patterns under different biological conditions in various organisms.”
Expression Atlas update—an integrated database of gene and protein expression in humans, animals and plants (2015, background): “Expression Atlas (2) is a further development of its predecessor, Gene Expression Atlas (1) launched by the European Bioinformatics Institute (EMBL-EBI) in 2008, and continues its original remit as a value-added database for querying gene expression across tissues, cell types and cell lines under va”
The Ensembl Variant Effect Predictor (2016, methodology): “For example an experimental plugin, GXA.pm, uses data from the Expression Atlas project (Petryszak et al. 2014) to indicate expression levels across tissues for many transcripts, which can be used to filter transcript isoforms.”
Integrative Analysis Identifies Four Molecular and Clinical Subsets in Uveal Melanoma. (2018, methodology): “, 2010): Data from the Gene Expression Atlas (Petryszak et al., 2014) was used to filter the inferred links in the ChEA database.”