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Nature. 2018 Oct;562(7726):203-209. doi: 10.1038/s41586-018-0579-z. Epub 2018 Oct 10.

The UK Biobank resource with deep phenotyping and genomic data.

Author information

1
Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
2
Procter & Gamble, Brussels, Belgium.
3
Department of Statistics, University of Oxford, Oxford, UK.
4
Melbourne Integrative Genomics and the Schools of Mathematics and Statistics, and BioSciences, The University of Melbourne, Parkville, Victoria, Australia.
5
Murdoch Children's Research Institute, Parkville, Victoria, Australia.
6
Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland.
7
Swiss Institute of Bioinformatics, University of Geneva, Geneva, Switzerland.
8
Institute of Genetics and Genomics in Geneva, University of Geneva, Geneva, Switzerland.
9
Illumina Ltd, Chesterford Research Park, Little Chesterford, Essex, UK.
10
Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, John Radcliffe Hospital, University of Oxford, Oxford, UK.
11
UK Biobank, Adswood, Stockport, Cheshire, UK.
12
Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
13
Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK. marchini@stats.ox.ac.uk.
14
Department of Statistics, University of Oxford, Oxford, UK. marchini@stats.ox.ac.uk.

Abstract

The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.

PMID:
30305743
DOI:
10.1038/s41586-018-0579-z

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