Data quality control in genetic case-control association studies

By C. Anderson, F. Pettersson, G. Clarke, Lon R. Cardon, Andrew P. Morris, Krina T. Zondervan. Nature Protocols, 2010

1,348 citations recorded by the source corpus.

This protocol details the steps for data quality assessment and control that are typically carried out during case-control association studies. The steps described involve the identification and removal of DNA samples and markers that introduce bias. These critical steps are paramount to the success of a case-control study and are necessary before statistically testing for association. We describe how to use PLINK, a tool for handling SNP data, to perform assessments of failure rate per individual and per SNP and to assess the degree of relatedness between individuals. We also detail other quality-control procedures, including the use of SMARTPCA software for the identification of ancestral outliers. These platforms were selected because they are user-friendly, widely used and computationally efficient. Steps needed to detect and establish a disease association using case-control data are not discussed here. Issues concerning study design and marker selection in case-control studies have been discussed in our earlier protocols. This protocol, which is routinely used in our labs, should take approximately 8 h to complete.

Subfields: Genetics

View Paper: https://www.semanticscholar.org/paper/4012d82a0f5801f30877607340879afd9f92d1d0

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Citations in the corpus

Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: A multivariable Mendelian randomisation analysis (2020, methodology): “GWAS analyses were conducted in UKBB participants of European descent based on Kmeans clustering (K = 4) after standard exclusions including withdrawn consent, mismatch between genetic and reported sex, and putative sex chromosome aneuploidy [33].”
Genome-wide association studies in ancestrally diverse populations: opportunities, methods, pitfalls, and recommendations. (2019, background): “Several guides to quality control of genotype data exist in the literature (Anderson et al., 2010; de Bakker et al., 2008; Laurie et al., 2010; Turner et al., 2011).”
Basic statistical analysis in genetic case-control studies (2011, methodology): “SNPs with a missing rate > 10%, a MAF 1% or an HWE P value 1 × 10 − 5 have already been excluded.”
A tutorial on conducting genome‐wide association studies: Quality control and statistical analysis (2018, neutral): “However, for a population based sample we suggest to use a pi ‐ hat threshold of 0.2, which in line with the literature (Anderson et al., 2010; Guo et al., 2014).”
MAGMA: Generalized Gene-Set Analysis of GWAS Data (2015, positive): “The data was cleaned according to the protocol described by Anderson [22], resulting in a sample of 1,694 cases and 2,917 controls with data for 403,227 SNPs.”