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      ENCODE data at the ENCODE portal

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          Abstract

          The Encyclopedia of DNA Elements (ENCODE) Project is in its third phase of creating a comprehensive catalog of functional elements in the human genome. This phase of the project includes an expansion of assays that measure diverse RNA populations, identify proteins that interact with RNA and DNA, probe regions of DNA hypersensitivity, and measure levels of DNA methylation in a wide range of cell and tissue types to identify putative regulatory elements. To date, results for almost 5000 experiments have been released for use by the scientific community. These data are available for searching, visualization and download at the new ENCODE Portal ( www.encodeproject.org). The revamped ENCODE Portal provides new ways to browse and search the ENCODE data based on the metadata that describe the assays as well as summaries of the assays that focus on data provenance. In addition, it is a flexible platform that allows integration of genomic data from multiple projects. The portal experience was designed to improve access to ENCODE data by relying on metadata that allow reusability and reproducibility of the experiments.

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          Most cited references15

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          BigWig and BigBed: enabling browsing of large distributed datasets

          Summary: BigWig and BigBed files are compressed binary indexed files containing data at several resolutions that allow the high-performance display of next-generation sequencing experiment results in the UCSC Genome Browser. The visualization is implemented using a multi-layered software approach that takes advantage of specific capabilities of web-based protocols and Linux and UNIX operating systems files, R trees and various indexing and compression tricks. As a result, only the data needed to support the current browser view is transmitted rather than the entire file, enabling fast remote access to large distributed data sets. Availability and implementation: Binaries for the BigWig and BigBed creation and parsing utilities may be downloaded at http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/. Source code for the creation and visualization software is freely available for non-commercial use at http://hgdownload.cse.ucsc.edu/admin/jksrc.zip, implemented in C and supported on Linux. The UCSC Genome Browser is available at http://genome.ucsc.edu Contact: ann@soe.ucsc.edu Supplementary information: Supplementary byte-level details of the BigWig and BigBed file formats are available at Bioinformatics online. For an in-depth description of UCSC data file formats and custom tracks, see http://genome.ucsc.edu/FAQ/FAQformat.html and http://genome.ucsc.edu/goldenPath/help/hgTracksHelp.html
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            Track data hubs enable visualization of user-defined genome-wide annotations on the UCSC Genome Browser

            Summary: Track data hubs provide an efficient mechanism for visualizing remotely hosted Internet-accessible collections of genome annotations. Hub datasets can be organized, configured and fully integrated into the University of California Santa Cruz (UCSC) Genome Browser and accessed through the familiar browser interface. For the first time, individuals can use the complete browser feature set to view custom datasets without the overhead of setting up and maintaining a mirror. Availability and implementation: Source code for the BigWig, BigBed and Genome Browser software is freely available for non-commercial use at http://hgdownload.cse.ucsc.edu/admin/jksrc.zip, implemented in C and supported on Linux. Binaries for the BigWig and BigBed creation and parsing utilities may be downloaded at http://hgdownload.cse.ucsc.edu/admin/exe/. Binary Alignment/Map (BAM) and Variant Call Format (VCF)/tabix utilities are available from http://samtools.sourceforge.net/ and http://vcftools.sourceforge.net/. The UCSC Genome Browser is publicly accessible at http://genome.ucsc.edu. Contact: donnak@soe.ucsc.edu
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              BioProject and BioSample databases at NCBI: facilitating capture and organization of metadata

              As the volume and complexity of data sets archived at NCBI grow rapidly, so does the need to gather and organize the associated metadata. Although metadata has been collected for some archival databases, previously, there was no centralized approach at NCBI for collecting this information and using it across databases. The BioProject database was recently established to facilitate organization and classification of project data submitted to NCBI, EBI and DDBJ databases. It captures descriptive information about research projects that result in high volume submissions to archival databases, ties together related data across multiple archives and serves as a central portal by which to inform users of data availability. Concomitantly, the BioSample database is being developed to capture descriptive information about the biological samples investigated in projects. BioProject and BioSample records link to corresponding data stored in archival repositories. Submissions are supported by a web-based Submission Portal that guides users through a series of forms for input of rich metadata describing their projects and samples. Together, these databases offer improved ways for users to query, locate, integrate and interpret the masses of data held in NCBI's archival repositories. The BioProject and BioSample databases are available at http://www.ncbi.nlm.nih.gov/bioproject and http://www.ncbi.nlm.nih.gov/biosample, respectively.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                04 January 2016
                02 November 2015
                02 November 2015
                : 44
                : Database issue , Database issue
                : D726-D732
                Affiliations
                [1 ]Stanford University School of Medicine, Department of Genetics, Stanford, CA, 94305, USA
                [2 ]University of California at Santa Cruz, Center for Biomolecular Science and Engineering, Santa Cruz, CA, 95064, USA
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +1 650 723 7541; Email: cherry@ 123456stanford.edu
                Author information
                http://orcid.org/0000-0002-2406-2623
                http://orcid.org/0000-0001-5951-5955
                http://orcid.org/0000-0002-0144-0564
                http://orcid.org/0000-0001-5094-282X
                http://orcid.org/0000-0003-3361-3594
                http://orcid.org/0000-0001-5025-5886
                http://orcid.org/0000-0003-0627-1859
                http://orcid.org/0000-0002-5819-8342
                http://orcid.org/0000-0001-6382-9738
                http://orcid.org/0000-0002-1420-0754
                http://orcid.org/0000-0002-7328-1283
                http://orcid.org/0000-0002-2592-2090
                http://orcid.org/0000-0002-8649-6611
                http://orcid.org/0000-0002-1775-4998
                http://orcid.org/0000-0001-9163-5180
                Article
                10.1093/nar/gkv1160
                4702836
                26527727
                8a5ef11d-8a24-4038-90f3-000cd06c92b3
                © The Author(s) 2015. 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 ( 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
                : 19 October 2015
                : 7 October 2015
                : 14 August 2015
                Page count
                Pages: 7
                Categories
                Database Issue
                Custom metadata
                04 January 2016

                Genetics
                Genetics

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