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      Ensembl 2016

      1 , 1 , 1 , 1 , 2 , 1 , 1 , 1 , 2 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 2 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 2 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 2 , *

      Nucleic Acids Research

      Oxford University Press

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          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 Ensembl project ( http://www.ensembl.org) is a system for genome annotation, analysis, storage and dissemination designed to facilitate the access of genomic annotation from chordates and key model organisms. It provides access to data from 87 species across our main and early access Pre! websites. This year we introduced three newly annotated species and released numerous updates across our supported species with a concentration on data for the latest genome assemblies of human, mouse, zebrafish and rat. We also provided two data updates for the previous human assembly, GRCh37, through a dedicated website ( http://grch37.ensembl.org). Our tools, in particular the VEP, have been improved significantly through integration of additional third party data. REST is now capable of larger-scale analysis and our regulatory data BioMart can deliver faster results. The website is now capable of displaying long-range interactions such as those found in cis-regulated datasets. Finally we have launched a website optimized for mobile devices providing views of genes, variants and phenotypes. Our data is made available without restriction and all code is available from our GitHub organization site ( http://github.com/Ensembl) under an Apache 2.0 license.

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          Most cited references 47

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            An Integrated Encyclopedia of DNA Elements in the Human Genome

            Summary The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure, and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall the project provides new insights into the organization and regulation of our genes and genome, and an expansive resource of functional annotations for biomedical research.
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              An integrated map of genetic variation from 1,092 human genomes

              Summary Through characterising the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help understand the genetic contribution to disease. We describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methodologies to integrate information across multiple algorithms and diverse data sources we provide a validated haplotype map of 38 million SNPs, 1.4 million indels and over 14 thousand larger deletions. We show that individuals from different populations carry different profiles of rare and common variants and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways and that each individual harbours hundreds of rare non-coding variants at conserved sites, such as transcription-factor-motif disrupting changes. This resource, which captures up to 98% of accessible SNPs at a frequency of 1% in populations of medical genetics focus, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations.
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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
                19 December 2015
                19 December 2015
                : 44
                : Database issue , Database issue
                : D710-D716
                Affiliations
                [1 ]European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
                [2 ]Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +44 1223 492581; Fax: +44 1223 494494; Email: flicek@ 123456ebi.ac.uk
                Article
                10.1093/nar/gkv1157
                4702834
                26687719
                © 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.

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                Pages: 7
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                Database Issue
                Custom metadata
                04 January 2016

                Genetics

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