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

• Published in: Genetic epidemiology Vol. 34; no. 6; pp. 591 - 602
• Main Authors: Laurie, Cathy C., Doheny, Kimberly F., Mirel, Daniel B., Pugh, Elizabeth W., Bierut, Laura J., Bhangale, Tushar, Boehm, Frederick, Caporaso, Neil E., Cornelis, Marilyn C., Edenberg, Howard J., Gabriel, Stacy B., Harris, Emily L., Hu, Frank B., Jacobs, Kevin B., Kraft, Peter, Landi, Maria Teresa, Lumley, Thomas, Manolio, Teri A., McHugh, Caitlin, Painter, Ian, Paschall, Justin, Rice, John P., Rice, Kenneth M., Zheng, Xiuwen, Weir, Bruce S.
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.09.2010
• Subjects: Aneuploidy; Case-Control Studies; chromosome aberration; Chromosome Aberrations; DNA probes; DNA sample quality; Female; Gene Frequency; Genetic variance; Genetic Variation; Genetics, Population; Genome-Wide Association Study - methods; Genome-Wide Association Study - standards; Genotype; Genotypes; Genotyping; genotyping artifact; GWAS; Hardy-Weinberg equilibrium; Humans; Lung Neoplasms - genetics; Male; Polymorphism, Single Nucleotide; Principal components analysis; Quality Control; Sex Chromosome Aberrations - statistics & numerical data; Sex chromosomes; Single-nucleotide polymorphism; Substance-Related Disorders - genetics
• ISSN: 0741-0395; 1098-2272; 1098-2272
• DOI: 10.1002/gepi.20516

Genome‐wide scans of nucleotide variation in human subjects are providing an increasing number of replicated associations with complex disease traits. Most of the variants detected have small effects and, collectively, they account for a small fraction of the total genetic variance. Very large sample sizes are required to identify and validate findings. In this situation, even small sources of systematic or random error can cause spurious results or obscure real effects. The need for careful attention to data quality has been appreciated for some time in this field, and a number of strategies for quality control and quality assurance (QC/QA) have been developed. Here we extend these methods and describe a system of QC/QA for genotypic data in genome‐wide association studies (GWAS). This system includes some new approaches that (1) combine analysis of allelic probe intensities and called genotypes to distinguish gender misidentification from sex chromosome aberrations, (2) detect autosomal chromosome aberrations that may affect genotype calling accuracy, (3) infer DNA sample quality from relatedness and allelic intensities, (4) use duplicate concordance to infer SNP quality, (5) detect genotyping artifacts from dependence of Hardy‐Weinberg equilibrium test P‐values on allelic frequency, and (6) demonstrate sensitivity of principal components analysis to SNP selection. The methods are illustrated with examples from the “Gene Environment Association Studies” (GENEVA) program. The results suggest several recommendations for QC/QA in the design and execution of GWAS. Genet. Epidemiol. 34: 591–602, 2010. © 2010 Wiley‐Liss, Inc.