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      DeepBlue epigenomic data server: programmatic data retrieval and analysis of epigenome region sets

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          Abstract

          Large amounts of epigenomic data are generated under the umbrella of the International Human Epigenome Consortium, which aims to establish 1000 reference epigenomes within the next few years. These data have the potential to unravel the complexity of epigenomic regulation. However, their effective use is hindered by the lack of flexible and easy-to-use methods for data retrieval. Extracting region sets of interest is a cumbersome task that involves several manual steps: identifying the relevant experiments, downloading the corresponding data files and filtering the region sets of interest. Here we present the DeepBlue Epigenomic Data Server, which streamlines epigenomic data analysis as well as software development. DeepBlue provides a comprehensive programmatic interface for finding, selecting, filtering, summarizing and downloading region sets. It contains data from four major epigenome projects, namely ENCODE, ROADMAP, BLUEPRINT and DEEP. DeepBlue comes with a user manual, examples and a well-documented application programming interface (API). The latter is accessed via the XML-RPC protocol supported by many programming languages. To demonstrate usage of the API and to enable convenient data retrieval for non-programmers, we offer an optional web interface. DeepBlue can be openly accessed at http://deepblue.mpi-inf.mpg.de.

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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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            Uberon, an integrative multi-species anatomy ontology

            We present Uberon, an integrated cross-species ontology consisting of over 6,500 classes representing a variety of anatomical entities, organized according to traditional anatomical classification criteria. The ontology represents structures in a species-neutral way and includes extensive associations to existing species-centric anatomical ontologies, allowing integration of model organism and human data. Uberon provides a necessary bridge between anatomical structures in different taxa for cross-species inference. It uses novel methods for representing taxonomic variation, and has proved to be essential for translational phenotype analyses. Uberon is available at http://uberon.org
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              Modeling sample variables with an Experimental Factor Ontology

              Motivation: Describing biological sample variables with ontologies is complex due to the cross-domain nature of experiments. Ontologies provide annotation solutions; however, for cross-domain investigations, multiple ontologies are needed to represent the data. These are subject to rapid change, are often not interoperable and present complexities that are a barrier to biological resource users. Results: We present the Experimental Factor Ontology, designed to meet cross-domain, application focused use cases for gene expression data. We describe our methodology and open source tools used to create the ontology. These include tools for creating ontology mappings, ontology views, detecting ontology changes and using ontologies in interfaces to enhance querying. The application of reference ontologies to data is a key problem, and this work presents guidelines on how community ontologies can be presented in an application ontology in a data-driven way. Availability: http://www.ebi.ac.uk/efo Contact: malone@ebi.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
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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
                15 April 2016
                15 April 2016
                : 44
                : Web Server issue
                : W581-W586
                Affiliations
                [1 ]Max Planck Institute for Informatics, 66123 Saarbrücken, Germany
                [2 ]Graduate School of Computer Science, Saarland University, 66123 Saarbrücken, Germany
                [3 ]CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria
                [4 ]Department of Laboratory Medicine, Medical University of Vienna, 1090 Vienna, Austria
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +49 681 9325 3008; Fax: +49 681 9325 3099; Email: felipe.albrecht@ 123456mpi-inf.mpg.de
                Author information
                http://orcid.org/0000-0002-5737-8405
                http://orcid.org/0000-0002-0941-4168
                Article
                10.1093/nar/gkw211
                4987868
                27084938
                df0e88f1-db09-45b9-8923-02a4451ebc53
                © 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-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 19 March 2016
                : 02 February 2016
                Page count
                Pages: 6
                Categories
                Web Server issue
                Custom metadata
                08 July 2016

                Genetics
                Genetics

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