Development of tools for automated collection, integration and analysis of genetic data in ALS

    Student thesis: Doctoral ThesisDoctor of Philosophy

    Abstract


    Amyotrophic Lateral Sclerosis (ALS), also known as Lou Gehrig’s disease, typically leads to death within 3-5 years of symptom onset. Understanding what causes ALS has been a challenge, but more research in this area, enhanced by advanced technology like high-throughput next generation sequencing, is paving the way for better information and direction. The volume of data generated by genetics researchers has dramatically increased, largely because of increased opportunities for collaboration. ALSoD, a widely used online genetics database for collating, analysing and integrating ALS data, has been updated with analytics tools and is able to portray the data graphically to users. Mutations and other gene variants have been mapped to genomic coordinates, and the inclusion of dbSNP ids has been implemented to facilitate the integration of data from
    numerous public sources. To increase the usability and functionality of ALSoD, population frequency of each variant found in the 1000 Genome Project and Exome Variation Server (EVS) databases is displayed. To contribute to a better understanding of the pathogenesis of ALS, links to information on animal models are also available. Furthermore, ALSoD can now be viewed on mobile devices and for Android platforms a mobile app is also available.
    Date of Award2014
    Original languageEnglish
    Awarding Institution
    • King's College London
    SupervisorJohn Powell (Supervisor) & Ammar Al-Chalabi (Supervisor)

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