Shared genomics: High performance computing for distributed insights in genomic medical research

David C. Hoyle, Mark Delderfield, Lee Kitching, Gareth Smith, Iain Buchan

    Research output: Contribution to journalArticlepeer-review

    Abstract

    The study of the genetics of diseases is entering a new era. Increasingly, genome-wide association studies are being used to identify positions within the human genome that have a link with a disease condition. The number of genomic locations studied means that High Performance Computing (HPC) solutions will have to increasingly be used in the statistical analysis of these data sets. Understanding the biomedical implications of the statistical analysis will also require heavy use of bioinformatics annotation tools. In this paper we report the outcome of developing HPC statistical genetics analysis codes for use by clinical researchers. Statistical results are automatically annotated with relevant biological information by calling multiple web-services orchestrated via pre-existing scientific workflows. Access to the HPC codes and bioinformatics annotation processes is via a client Workbench which hides as much as possible from the user the HPC infrastructure and bioinformatics annotation processes, whilst aiding the exchange of ideas and results between stakeholders. © 2009 The authors and IOS Press. All rights reserved.
    Original languageEnglish
    Pages (from-to)232-241
    Number of pages9
    JournalStudies in Health Technology and Informatics
    Volume147
    DOIs
    Publication statusPublished - 2009

    Keywords

    • Genome-wide association study
    • HPC
    • Statistical genetics

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