Expression Atlas: gene and protein expression across multiple studies and organisms

By I. Papatheodorou, Nuno A. Fonseca, M. Keays, Y Amy Tang, E. Barrera, Wojciech Bazant, Melissa L. Burke, Anja Füllgrabe, Alfonso Muñoz-Pomer Fuentes, Nancy George and 12 more. Nucleic Acids Res., 2017

361 citations recorded by the source corpus.

Abstract Expression Atlas (http://www.ebi.ac.uk/gxa) is an added value database that provides information about gene and protein expression in different species and contexts, such as tissue, developmental stage, disease or cell type. The available public and controlled access data sets from different sources are curated and re-analysed using standardized, open source pipelines and made available for queries, download and visualization. As of August 2017, Expression Atlas holds data from 3,126 studies across 33 different species, including 731 from plants. Data from large-scale RNA sequencing studies including Blueprint, PCAWG, ENCODE, GTEx and HipSci can be visualized next to each other. In Expression Atlas, users can query genes or gene-sets of interest and explore their expression across or within species, tissues, developmental stages in a constitutive or differential context, representing the effects of diseases, conditions or experimental interventions. All processed data matrices are available for direct download in tab-delimited format or as R-data. In addition to the web interface, data sets can now be searched and downloaded through the Expression Atlas R package. Novel features and visualizations include the on-the-fly analysis of gene set overlaps and the option to view gene co-expression in experiments investigating constitutive gene expression across tissues or other conditions.

Subfields: Molecular Biology

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Citations in the corpus

Complex Portal 2018: extended content and enhanced visualization tools for macromolecular complexes (2018, methodology): “Finally, the Body Map tool from the Gene Expression Atlas displays tissue-specific gene expression data for all members of the complex for most multi-cellular species (16).”
The ProteomeXchange consortium in 2020: enabling ‘big data’ approaches in proteomics (2019, background): “Figure 1 highlights some of those resources, including: (i) Protein knowledge bases (UniProt (19) and neXtProt (33)), to support information about each protein’s experimental evidence; (ii) Genome browsers (Ensembl (20) and UCSC Genome Browser (34)), where it is possible to integrate proteomics and ”
ArrayExpress update – from bulk to single-cell expression data (2018, methodology): “Funding for open access charge: the Wellcome Trust Biomedical Resources grant Single Cell Gene Expression Atlas [108437/Z/15/Z].”
The PRIDE database and related tools and resources in 2019: improving support for quantification data (2018, methodology): “At the time of writing, 15 quantitative proteomics datasets have already been integrated into the Expression Atlas, an EMBL-EBI added value database that provides information about gene and protein expression in different species and contexts (11).”
Expression Atlas update: from tissues to single cells (2019, background): “Since the last Expression Atlas update in 2017 (9), the main devel-”
Open Targets Platform: new developments and updates two years on (2018, methodology): “The first tab shows RNA and protein expression data side by side for a quicker comparison (Figure 3A).”
miRDB: an online database for prediction of functional microRNA targets (2019, methodology): “Specifically, we downloaded RNA-seq gene expression profiling data from two large-scale transcriptome studies (13,14) that were deposited in Expression Atlas (15).”