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      The variant call format and VCFtools

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          Abstract

          Summary: The variant call format (VCF) is a generic format for storing DNA polymorphism data such as SNPs, insertions, deletions and structural variants, together with rich annotations. VCF is usually stored in a compressed manner and can be indexed for fast data retrieval of variants from a range of positions on the reference genome. The format was developed for the 1000 Genomes Project, and has also been adopted by other projects such as UK10K, dbSNP and the NHLBI Exome Project. VCFtools is a software suite that implements various utilities for processing VCF files, including validation, merging, comparing and also provides a general Perl API.

          Availability: http://vcftools.sourceforge.net

          Contact: rd@ 123456sanger.ac.uk

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          Most cited references1

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          A standard variation file format for human genome sequences

          Here we describe the Genome Variation Format (GVF) and the 10Gen dataset. GVF, an extension of Generic Feature Format version 3 (GFF3), is a simple tab-delimited format for DNA variant files, which uses Sequence Ontology to describe genome variation data. The 10Gen dataset, ten human genomes in GVF format, is freely available for community analysis from the Sequence Ontology website and from an Amazon elastic block storage (EBS) snapshot for use in Amazon's EC2 cloud computing environment.
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            Author and article information

            Journal
            Bioinformatics
            bioinformatics
            bioinfo
            Bioinformatics
            Oxford University Press
            1367-4803
            1367-4811
            1 August 2011
            7 June 2011
            7 June 2011
            : 27
            : 15
            : 2156-2158
            Affiliations
            1Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge CB10 1SA, 2Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK, 3Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, 4Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02141, 5Department of Biology, Boston College, MA 02467, 6National Institutes of Health National Center for Biotechnology Information, MD 20894, USA and 7Department of Statistics, University of Oxford, Oxford OX1 3TG, UK
            Author notes
            * To whom correspondence should be addressed.

            † The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.

            Associate Editor: John Quackenbush

            Article
            btr330
            10.1093/bioinformatics/btr330
            3137218
            21653522
            6fd9700a-8c32-4897-a9d2-68ddc973fd18
            © The Author(s) 2011. Published by Oxford University Press.

            This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

            History
            : 28 October 2010
            : 4 May 2011
            : 28 May 2011
            Page count
            Pages: 3
            Categories
            Applications Note
            Sequence Analysis

            Bioinformatics & Computational biology
            Bioinformatics & Computational biology

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