• DocumentCode
    174844
  • Title

    Toward Efficient Variant Calling Inside Main-Memory Database Systems

  • Author

    Dorok, Sebastian ; Bress, Sebastian ; Saake, Gunter

  • Author_Institution
    Bayer Pharma AG, Magdeburg, Germany
  • fYear
    2014
  • fDate
    1-5 Sept. 2014
  • Firstpage
    41
  • Lastpage
    45
  • Abstract
    Mutations in genomes indicate predisposition for diseases or effects on efficacy of drugs. A variant calling algorithm determines possible mutations in sample genomes. Afterwards, scientists have to decide about the impact of these mutations. Certainly, many different variant calling algorithms exist that generate different outputs due to different sequence alignments as input and parameterizations of variant calling algorithms. Thus, a combination of variant calling results is necessary to provide a more complete set of mutations than single algorithm runs can provide. Therefore, a system is required that facilitates the integration and parameterization of different variant calling algorithms and processing of different sequence alignments. Moreover, against the backdrop of ever increasing amounts of available genome sequencing data, such a system must provide matured database management capabilities to enable flexible and efficient analyses while keeping data consistent. In this paper, we present a first approach to integrate variant calling into a main-memory database management system that allows for calling variants via SQL.
  • Keywords
    SQL; bioinformatics; database management systems; genomics; SQL; genome mutations; genome sequencing data; main-memory database management system; variant calling algorithm; Algorithm design and analysis; Bioinformatics; Database systems; Genomics; Runtime; Standards; Genome Analysis; Main-Memory Database Systems; Variant Calling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Database and Expert Systems Applications (DEXA), 2014 25th International Workshop on
  • Conference_Location
    Munich
  • ISSN
    1529-4188
  • Print_ISBN
    978-1-4799-5721-7
  • Type

    conf

  • DOI
    10.1109/DEXA.2014.25
  • Filename
    6974824