scholarly journals Quality control and quality assurance in genotypic data for genome-wide association studies

2010 ◽  
Vol 34 (6) ◽  
pp. 591-602 ◽  
Author(s):  
Cathy C. Laurie ◽  
Kimberly F. Doheny ◽  
Daniel B. Mirel ◽  
Elizabeth W. Pugh ◽  
Laura J. Bierut ◽  
...  
Keyword(s):  
Quality Control ◽  
Quality Assurance ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals GWASTools: an R/Bioconductor package for quality control and analysis of genome-wide association studies

2012 ◽  
Vol 28 (24) ◽  
pp. 3329-3331 ◽  
Author(s):  
S. M. Gogarten ◽  
T. Bhangale ◽  
M. P. Conomos ◽  
C. A. Laurie ◽  
C. P. McHugh ◽  
...  
Keyword(s):  
Quality Control ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Bioconductor Package ◽  
Genome Wide

scholarly journals Genome-wide genetic data on ~500,000 UK Biobank participants

2017 ◽  
Author(s):  
Clare Bycroft ◽  
Colin Freeman ◽  
Desislava Petkova ◽  
Gavin Band ◽  
Lloyd T. Elliott ◽  
...  
Keyword(s):  
Quality Control ◽  
Allelic Variation ◽  
Association Studies ◽  
Genetic Data ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genotype Data ◽  
Uk Biobank ◽  
Genome Wide ◽  
Wide Range

AbstractThe UK Biobank project is a large prospective cohort study of ~500,000 individuals from across the United Kingdom, aged between 40-69 at recruitment. A rich variety of phenotypic and health-related information is available on each participant, making the resource unprecedented in its size and scope. Here we describe the genome-wide genotype data (~805,000 markers) collected on all individuals in the cohort and its quality control procedures. Genotype data on this scale offers novel opportunities for assessing quality issues, although the wide range of ancestries of the individuals in the cohort also creates particular challenges. We also conducted a set of analyses that reveal properties of the genetic data – such as population structure and relatedness – that can be important for downstream analyses. In addition, we phased and imputed genotypes into the dataset, using computationally efficient methods combined with the Haplotype Reference Consortium (HRC) and UK10K haplotype resource. This increases the number of testable variants by over 100-fold to ~96 million variants. We also imputed classical allelic variation at 11 human leukocyte antigen (HLA) genes, and as a quality control check of this imputation, we replicate signals of known associations between HLA alleles and many common diseases. We describe tools that allow efficient genome-wide association studies (GWAS) of multiple traits and fast phenome-wide association studies (PheWAS), which work together with a new compressed file format that has been used to distribute the dataset. As a further check of the genotyped and imputed datasets, we performed a test-case genome-wide association scan on a well-studied human trait, standing height.

scholarly journals A quality control algorithm for filtering SNPs in genome-wide association studies

2010 ◽  
Vol 26 (14) ◽  
pp. 1731-1737 ◽  
Author(s):  
Monnat Pongpanich ◽  
Patrick F. Sullivan ◽  
Jung-Ying Tzeng
Keyword(s):  
Quality Control ◽  
Control Algorithm ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals A tutorial on conducting genome-wide association studies: Quality control and statistical analysis

2018 ◽  
Vol 27 (2) ◽  
pp. e1608 ◽  
Author(s):  
Andries T. Marees ◽  
Hilde de Kluiver ◽  
Sven Stringer ◽  
Florence Vorspan ◽  
Emmanuel Curis ◽  
...  
Keyword(s):  
Quality Control ◽  
Statistical Analysis ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide
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