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      New developments on the Encyclopedia of DNA Elements (ENCODE) data portal

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          Abstract

          The Encyclopedia of DNA Elements (ENCODE) is an ongoing collaborative research project aimed at identifying all the functional elements in the human and mouse genomes. Data generated by the ENCODE consortium are freely accessible at the ENCODE portal ( https://www.encodeproject.org/), which is developed and maintained by the ENCODE Data Coordinating Center (DCC). Since the initial portal release in 2013, the ENCODE DCC has updated the portal to make ENCODE data more findable, accessible, interoperable and reusable. Here, we report on recent updates, including new ENCODE data and assays, ENCODE uniform data processing pipelines, new visualization tools, a dataset cart feature, unrestricted public access to ENCODE data on the cloud (Amazon Web Services open data registry, https://registry.opendata.aws/encode-project/) and more comprehensive tutorials and documentation.

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          Most cited references12

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          Gene Ontology: tool for the unification of biology

          Michael Ashburner, Catherine A. Ball, Judith Blake … (2002)
          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Chromatin-state discovery and genome annotation with ChromHMM.

            Jason Ernst, Manolis Kellis (2017)
            Noncoding DNA regions have central roles in human biology, evolution, and disease. ChromHMM helps to annotate the noncoding genome using epigenomic information across one or multiple cell types. It combines multiple genome-wide epigenomic maps, and uses combinatorial and spatial mark patterns to infer a complete annotation for each cell type. ChromHMM learns chromatin-state signatures using a multivariate hidden Markov model (HMM) that explicitly models the combinatorial presence or absence of each mark. ChromHMM uses these signatures to generate a genome-wide annotation for each cell type by calculating the most probable state for each genomic segment. ChromHMM provides an automated enrichment analysis of the resulting annotations to facilitate the functional interpretations of each chromatin state. ChromHMM is distinguished by its modeling emphasis on combinations of marks, its tight integration with downstream functional enrichment analyses, its speed, and its ease of use. Chromatin states are learned, annotations are produced, and enrichments are computed within 1 d.
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              Entrez Gene: gene-centered information at NCBI

              Donna R. Maglott, Jim Ostell, Kim D. Pruitt … (2006)
              Entrez Gene () is NCBI's database for gene-specific information. Entrez Gene includes records from genomes that have been completely sequenced, that have an active research community to contribute gene-specific information or that are scheduled for intense sequence analysis. The content of Entrez Gene represents the result of both curation and automated integration of data from NCBI's Reference Sequence project (RefSeq), from collaborating model organism databases and from other databases within NCBI. Records in Entrez Gene are assigned unique, stable and tracked integers as identifiers. The content (nomenclature, map location, gene products and their attributes, markers, phenotypes and links to citations, sequences, variation details, maps, expression, homologs, protein domains and external databases) is provided via interactive browsing through NCBI's Entrez system, via NCBI's Entrez programing utilities (E-Utilities), and for bulk transfer by ftp.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (iso-abbrev): Nucleic Acids Res
                Journal ID (publisher-id): nar
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date (Print): 08 January 2020
                Publication date (Electronic): 12 November 2019
                Publication date PMC-release: 12 November 2019
                Volume: 48
                Issue: D1
                Pages: D882-D889
                Affiliations
                Department of Genetics, Stanford University , Stanford, CA 94305-5477, USA
                Author notes
                To whom correspondence should be addressed. Tel: +1 650 723 7541; Email: cherry@ 123456stanford.edu
                Author information
                http://orcid.org/0000-0001-6948-2042
                http://orcid.org/0000-0003-3361-3594
                http://orcid.org/0000-0001-5025-5886
                http://orcid.org/0000-0001-5094-282X
                http://orcid.org/0000-0002-8649-6611
                Article
                Publisher ID: gkz1062
                DOI: 10.1093/nar/gkz1062
                PMC ID: 7061942
                PubMed ID: 31713622
                SO-VID: 224cc7cb-2a7e-45b5-bb1d-29f52ecb9a49
                Copyright © © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.
                License:

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

                History
                Date accepted : 25 October 2019
                Date revision received : 18 October 2019
                Date received : 13 September 2019
                Page count
                Pages: 8
                Funding
                Funded by: National Human Genome Research Institute 10.13039/100000051
                Funded by: National Institutes of Health 10.13039/100000002
                Award ID: U24 HG009397
                Categories
                Subject: Database Issue

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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