Project description: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.

| S-EPMC6786975 | biostudies-literature

CIDR_NINDS High Throughput Genotyping Resource Access for Structural Hindbrain Disorders

Project description:CIDR_NINDS High Throughput Genotyping Resource Access for Structural Hindbrain Disorders

| PRJNA766103 | ENA

CIDR_NINDS High Throughput Genotyping Resource Access for Structural Hindbrain Disorders

Project description:CIDR_NINDS High Throughput Genotyping Resource Access for Structural Hindbrain Disorders

| PRJNA766104 | ENA

SEER Remote Access Pilot Test Data (2018)

Project description:SEER Remote Access Pilot Test Data (2018)

| PRJNA625583 | ENA

SEER Remote Access Pilot Test Data (2018)

Project description:SEER Remote Access Pilot Test Data (2018)

| PRJNA625584 | ENA

Curating a longitudinal research resource using linked primary care EHR data-a UK Biobank case study.

Project description:Primary care EHR data are often of clinical importance to cohort studies however they require careful handling. Challenges include determining the periods during which EHR data were collected. Participants are typically censored when they deregister from a medical practice, however, cohort studies wish to follow participants longitudinally including those that change practice. Using UK Biobank as an exemplar, we developed methodology to infer continuous periods of data collection and maximize follow-up in longitudinal studies. This resulted in longer follow-up for around 40% of participants with multiple registration records (mean increase of 3.8 years from the first study visit). The approach did not sacrifice phenotyping accuracy when comparing agreement between self-reported and EHR data. A diabetes mellitus case study illustrates how the algorithm supports longitudinal study design and provides further validation. We use UK Biobank data, however, the tools provided can be used for other conditions and studies with minimal alteration.

| S-EPMC8800530 | biostudies-literature

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