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      The Sequence Alignment/Map format and SAMtools

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          Abstract

          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@ 123456sanger.ac.uk

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          Author and article information

          Journal
          Bioinformatics
          bioinformatics
          bioinfo
          Bioinformatics
          Oxford University Press
          1367-4803
          1460-2059
          15 August 2009
          8 June 2009
          8 June 2009
          : 25
          : 16
          : 2078-2079
          Affiliations
          1 Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SA, UK, 2Broad Institute of MIT and Harvard, Cambridge, MA 02141, USA, 3Beijing Institute of Genomics, Chinese Academy of Science, Beijing 100029, China, 4Department of Computer Science, University of California Los Angeles, Los Angeles, CA 90095, 5Department of Biology, Boston College, Chestnut Hill, MA 02467, 6Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA and 7 http://1000genomes.org
          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: Alfonso Valencia

          Article
          btp352
          10.1093/bioinformatics/btp352
          2723002
          19505943
          96b7bc64-d0fc-44a2-9a95-f1a765358bc6

          This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

          Categories
          Applications Note
          Sequence Analysis

          Bioinformatics & Computational biology
          Bioinformatics & Computational biology

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