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    Data Descriptor: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

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    Author
    Flannick, J; Fuchsberger, C; Mahajan, A; Teslovich, TM; Agarwala, V; Gaulton, KJ; Caulkins, L; Koesterer, R; Ma, C; Moutsianas, L; ...
    Date
    2017-12-19
    Source Title
    Scientific Data
    Publisher
    NATURE PUBLISHING GROUP
    University of Melbourne Author/s
    McCarthy, Davis
    Affiliation
    School of Mathematics and Statistics
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Flannick, J., Fuchsberger, C., Mahajan, A., Teslovich, T. M., Agarwala, V., Gaulton, K. J., Caulkins, L., Koesterer, R., Ma, C., Moutsianas, L., McCarthy, D. J., Rivas, M. A., Perry, J. R. B., Sim, X., Blackwell, T. W., Robertson, N. R., Rayner, N. W., Cingolani, P., Locke, A. E. ,... McCarthy, M. I. (2017). Data Descriptor: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls. SCIENTIFIC DATA, 4 (1), https://doi.org/10.1038/sdata.2017.179.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/255578
    DOI
    10.1038/sdata.2017.179
    Abstract
    To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

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