6
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Expression Atlas update: gene and protein expression in multiple species

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The EMBL-EBI Expression Atlas is an added value knowledge base that enables researchers to answer the question of where (tissue, organism part, developmental stage, cell type) and under which conditions (disease, treatment, gender, etc) a gene or protein of interest is expressed. Expression Atlas brings together data from >4500 expression studies from >65 different species, across different conditions and tissues. It makes these data freely available in an easy to visualise form, after expert curation to accurately represent the intended experimental design, re-analysed via standardised pipelines that rely on open-source community developed tools. Each study's metadata are annotated using ontologies. The data are re-analyzed with the aim of reproducing the original conclusions of the underlying experiments. Expression Atlas is currently divided into Bulk Expression Atlas and Single Cell Expression Atlas. Expression Atlas contains data from differential studies (microarray and bulk RNA-Seq) and baseline studies (bulk RNA-Seq and proteomics), whereas Single Cell Expression Atlas is currently dedicated to Single Cell RNA-Sequencing (scRNA-Seq) studies. The resource has been in continuous development since 2009 and it is available at https://www.ebi.ac.uk/gxa.

          Related collections

          Most cited references33

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          The FAIR Guiding Principles for scientific data management and stewardship

          There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            The PRIDE database and related tools and resources in 2019: improving support for quantification data

            Abstract The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world’s largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeXchange (PX) consortium. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2016. In the last 3 years, public data sharing through PRIDE (as part of PX) has definitely become the norm in the field. In parallel, data re-use of public proteomics data has increased enormously, with multiple applications. We first describe the new architecture of PRIDE Archive, the archival component of PRIDE. PRIDE Archive and the related data submission framework have been further developed to support the increase in submitted data volumes and additional data types. A new scalable and fault tolerant storage backend, Application Programming Interface and web interface have been implemented, as a part of an ongoing process. Additionally, we emphasize the improved support for quantitative proteomics data through the mzTab format. At last, we outline key statistics on the current data contents and volume of downloads, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              NCBI GEO: archive for functional genomics data sets—update

              The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research community. The resource supports archiving of raw data, processed data and metadata which are indexed, cross-linked and searchable. All data are freely available for download in a variety of formats. GEO also provides several web-based tools and strategies to assist users to query, analyse and visualize data. This article reports current status and recent database developments, including the release of GEO2R, an R-based web application that helps users analyse GEO data.
                Bookmark

                Author and article information

                Contributors
                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                07 January 2022
                24 November 2021
                24 November 2021
                : 50
                : D1
                : D129-D140
                Affiliations
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                Cold Spring Harbor Laboratory , Cold Spring Harbor, NY 11724, USA
                Cold Spring Harbor Laboratory , Cold Spring Harbor, NY 11724, USA
                Cold Spring Harbor Laboratory , Cold Spring Harbor, NY 11724, USA
                USDA ARS NEA, Plant Soil & Nutrition Laboratory Research Unit , Ithaca, NY 14853, USA
                Wellcome Sanger Institute , Wellcome Genome Campus, Hinxton, UK
                Edinburgh Pathology, University of Edinburgh, Institute of Genetics & Cancer , Edinburgh, UK
                Department of Pathology and Medical Biology, GRIAC research institute, University of Groningen, University Medical Center Groningen , Groningen, Netherlands
                Wellcome Sanger Institute , Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                Wellcome Sanger Institute , Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute , EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
                Author notes
                To whom correspondence should be addressed. Tel: +44 0 1223 49 2568; Email: irenep@ 123456ebi.ac.uk

                The authors wish it to be known that, in their opinion, the first three authors should be regarded as joint First Authors.

                Author information
                https://orcid.org/0000-0002-9856-1679
                https://orcid.org/0000-0002-5777-9815
                https://orcid.org/0000-0002-8674-0039
                https://orcid.org/0000-0002-5989-6898
                https://orcid.org/0000-0002-7499-5368
                https://orcid.org/0000-0002-2513-5396
                https://orcid.org/0000-0001-9092-0852
                https://orcid.org/0000-0002-3905-4335
                https://orcid.org/0000-0001-7270-5470
                Article
                gkab1030
                10.1093/nar/gkab1030
                8728300
                34850121
                ca617d21-5bbe-49e8-bfa2-7cc4264b7ba3
                © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 19 November 2021
                : 11 October 2021
                : 17 September 2021
                Page count
                Pages: 12
                Funding
                Funded by: European Molecular Biology Laboratory, DOI 10.13039/100013060;
                Funded by: Wellcome Trust, DOI 10.13039/100010269;
                Award ID: 108437/Z/15/Z
                Award ID: 221401/Z/20/Z
                Award ID: 208391/Z/17/Z
                Funded by: BBSRC, DOI 10.13039/501100000268;
                Award ID: BB/P024599/1
                Award ID: BB/T019670/1
                Award ID: BB/T014563/1
                Funded by: National Science Foundation, DOI 10.13039/100000001;
                Award ID: IOS #1127112
                Funded by: Open Targets;
                Award ID: OTAR2-043
                Funded by: Chan Zuckerberg Initiative, DOI 10.13039/100014989;
                Funded by: European Union's H2020 Research and Innovation Program;
                Award ID: 874656
                Categories
                AcademicSubjects/SCI00010
                Database Issue

                Genetics
                Genetics

                Comments

                Comment on this article