Expression Atlas: gene and protein expression across multiple studies and organisms. Issue Volume 46:Issue D1(2018) (20th November 2017)

• Record Type: Journal Article
• Authors: Papatheodorou, Irene; Fonseca, Nuno A; Keays, Maria; Tang, Y Amy; Barrera, Elisabet; Bazant, Wojciech; Burke, Melissa; Füllgrabe, Anja; Fuentes, Alfonso Muñoz-Pomer; George, Nancy; Huerta, Laura; Koskinen, Satu; Mohammed, Suhaib; Geniza, Matthew; Preece, Justin; Jaiswal, Pankaj; Jarnuczak, Andrew F; Huber, Wolfgang; Stegle, Oliver; Vizcaino, Juan Antonio; Brazma, Alvis; Petryszak, Robert
• Is Part Of: Nucleic acids research. Volume 46:Issue D1(2018)
• Page Start: D246
• Page End: D251
• Publication Date: 2017-11-20
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkx1158
• Languages: English
• ISSNs: 0305-1048

Abstract

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.