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      Prospects of Fine-Mapping Trait-Associated Genomic Regions by Using Summary Statistics from Genome-wide Association Studies

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          Abstract

          During the past few years, various novel statistical methods have been developed for fine-mapping with the use of summary statistics from genome-wide association studies (GWASs). Although these approaches require information about the linkage disequilibrium (LD) between variants, there has not been a comprehensive evaluation of how estimation of the LD structure from reference genotype panels performs in comparison with that from the original individual-level GWAS data. Using population genotype data from Finland and the UK Biobank, we show here that a reference panel of 1,000 individuals from the target population is adequate for a GWAS cohort of up to 10,000 individuals, whereas smaller panels, such as those from the 1000 Genomes Project, should be avoided. We also show, both theoretically and empirically, that the size of the reference panel needs to scale with the GWAS sample size; this has important consequences for the application of these methods in ongoing GWAS meta-analyses and large biobank studies. We conclude by providing software tools and by recommending practices for sharing LD information to more efficiently exploit summary statistics in genetics research.

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          Author and article information

          Contributors
          Journal
          Am J Hum Genet
          Am. J. Hum. Genet
          American Journal of Human Genetics
          Elsevier
          0002-9297
          1537-6605
          05 October 2017
          21 September 2017
          : 101
          : 4
          : 539-551
          Affiliations
          [1 ]Institute for Molecular Medicine Finland, University of Helsinki, 00014 Helsinki, Finland
          [2 ]Department of Public Health, University of Helsinki, 00014 Helsinki, Finland
          [3 ]National Institute for Health and Welfare, 00271 Helsinki, Finland
          [4 ]Center for Life-Course Health Research and Northern Finland Cohort Center, Biocenter Oulu, University of Oulu, 90014 Oulu, Finland
          [5 ]Faculty of Medicine, University of Oulu, 90014 Oulu, Finland
          [6 ]Unit of Primary Care, Oulu University Hospital, 90220 Oulu, Finland
          [7 ]Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, W2 1PG, UK
          [8 ]Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, Cambridge, UK
          [9 ]Helsinki Institute for Information Technology and Department of Mathematics and Statistics, University of Helsinki, 00014 Helsinki, Finland
          Author notes
          []Corresponding author christian.benner@ 123456helsinki.fi
          [∗∗ ]Corresponding author matti.pirinen@ 123456helsinki.fi
          Article
          PMC5630179 PMC5630179 5630179 S0002-9297(17)30334-8
          10.1016/j.ajhg.2017.08.012
          5630179
          28942963
          1a3eb9e1-a545-4250-baad-85b0bfe0f8bb
          © 2017 American Society of Human Genetics.
          History
          : 21 March 2017
          : 17 August 2017
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