Integrating phenotypic data for depression

Amy Butler, Sarah Cohen-Woods, Anne Farmer, Peter McGuffin, Cathryn Lewis

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)


    The golden era of molecular genetic research brings about an explosion of phenotypic, genotypic and sequencing data. Building on the common aims to exploit understanding of human diseases, it also opens up an opportunity for scientific communities to share and combine research data. Genome-wide association studies (GWAS) have been widely used to locate genetic variants, which are susceptible for common diseases. In the field of medical genetics, many international collaborative consortiums have been established to conduct meta-analyses of GWAS results and to combine large genotypic data sets to perform mega genetic analyses. Having an integrated phenotype database is significant for exploiting the full potential of extensive genotypic data. In this paper, we aim to share our experience gained from integrating four heterogeneous sets of major depression phenotypic data onto the MySQL platform. These data sets constitute clinical data which had been gathered for various genetic studies for the past decade. We also highlight in this report some generic data handling techniques, the costs and benefits regarding the use of integrated phenotype database within our own institution and under the consortium framework.

    Original languageEnglish
    Pages (from-to)Art: 136
    Number of pages10
    JournalJournal of Integrative Bioinformatics
    Issue number3
    Publication statusPublished - 2010


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