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      The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update

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          Abstract

          High-throughput data production technologies, particularly ‘next-generation’ DNA sequencing, have ushered in widespread and disruptive changes to biomedical research. Making sense of the large datasets produced by these technologies requires sophisticated statistical and computational methods, as well as substantial computational power. This has led to an acute crisis in life sciences, as researchers without informatics training attempt to perform computation-dependent analyses. Since 2005, the Galaxy project has worked to address this problem by providing a framework that makes advanced computational tools usable by non experts. Galaxy seeks to make data-intensive research more accessible, transparent and reproducible by providing a Web-based environment in which users can perform computational analyses and have all of the details automatically tracked for later inspection, publication, or reuse. In this report we highlight recently added features enabling biomedical analyses on a large scale.

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          Most cited references14

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          Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences

          Increased reliance on computational approaches in the life sciences has revealed grave concerns about how accessible and reproducible computation-reliant results truly are. Galaxy http://usegalaxy.org, an open web-based platform for genomic research, addresses these problems. Galaxy automatically tracks and manages data provenance and provides support for capturing the context and intent of computational methods. Galaxy Pages are interactive, web-based documents that provide users with a medium to communicate a complete computational analysis.
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            Assembly: a resource for assembled genomes at NCBI

            The NCBI Assembly database (www.ncbi.nlm.nih.gov/assembly/) provides stable accessioning and data tracking for genome assembly data. The model underlying the database can accommodate a range of assembly structures, including sets of unordered contig or scaffold sequences, bacterial genomes consisting of a single complete chromosome, or complex structures such as a human genome with modeled allelic variation. The database provides an assembly accession and version to unambiguously identify the set of sequences that make up a particular version of an assembly, and tracks changes to updated genome assemblies. The Assembly database reports metadata such as assembly names, simple statistical reports of the assembly (number of contigs and scaffolds, contiguity metrics such as contig N50, total sequence length and total gap length) as well as the assembly update history. The Assembly database also tracks the relationship between an assembly submitted to the International Nucleotide Sequence Database Consortium (INSDC) and the assembly represented in the NCBI RefSeq project. Users can find assemblies of interest by querying the Assembly Resource directly or by browsing available assemblies for a particular organism. Links in the Assembly Resource allow users to easily download sequence and annotations for current versions of genome assemblies from the NCBI genomes FTP site.
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              The Taverna workflow suite: designing and executing workflows of Web Services on the desktop, web or in the cloud

              The Taverna workflow tool suite (http://www.taverna.org.uk) is designed to combine distributed Web Services and/or local tools into complex analysis pipelines. These pipelines can be executed on local desktop machines or through larger infrastructure (such as supercomputers, Grids or cloud environments), using the Taverna Server. In bioinformatics, Taverna workflows are typically used in the areas of high-throughput omics analyses (for example, proteomics or transcriptomics), or for evidence gathering methods involving text mining or data mining. Through Taverna, scientists have access to several thousand different tools and resources that are freely available from a large range of life science institutions. Once constructed, the workflows are reusable, executable bioinformatics protocols that can be shared, reused and repurposed. A repository of public workflows is available at http://www.myexperiment.org. This article provides an update to the Taverna tool suite, highlighting new features and developments in the workbench and the Taverna Server.
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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
                08 July 2016
                02 May 2016
                02 May 2016
                : 44
                : Web Server issue
                : W3-W10
                Affiliations
                [1 ]Department of Biology, Johns Hopkins University, Baltimore, MD USA
                [2 ]Institut de Biologie Paris-Seine, Université Pierre et Marie Curie, Paris, France
                [3 ]Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA
                [4 ]Department of Computer Science, Albert-Ludwigs-University, Freiburg, Freiburg, Germany
                [5 ]Center for Biological Systems Analysis (ZBSA), University of Freiburg, Freiburg, Germany
                [6 ]Academic Computing Services, Penn State University, University Park, PA, USA
                [7 ]Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, USA
                [8 ]The Genome Analysis Centre, Norwich, United Kingdom
                [9 ]The Computational Biology Institute, George Washington University, Washington DC, USA
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +1 571 553 0114; Email: jgoecks@ 123456gwu.edu
                Correspondence may also be addressed James Taylor. Tel: +1 410 516 0152; Email: james@ 123456taylorlab.org
                Correspondence may also be addressed Anton Nekrutenko. Tel: +1 814 865 4752; Email: anton@ 123456nekrut.org
                Article
                10.1093/nar/gkw343
                4987906
                27137889
                7ad825cd-5c42-41d2-aa48-16375dac333a
                © The Author(s) 2016. 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
                : 18 April 2016
                : 09 April 2016
                : 01 March 2016
                Page count
                Pages: 8
                Categories
                Web Server issue
                Custom metadata
                08 July 2016

                Genetics
                Genetics

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