How to link call rate and p-values for Hardy-Weinberg equilibrium as measures of genome-wide SNP data quality

Statistics in Medicine
Helmut FinnerChristian Gieger

Abstract

We study the link between two quality measures of SNP (single nucleotide polymorphism) data in genome-wide association (GWA) studies, that is, per SNP call rates (CR) and p-values for testing Hardy-Weinberg equilibrium (HWE). The aim is to improve these measures by applying methods based on realized randomized p-values, the false discovery rate and estimates for the proportion of false hypotheses. While exact non-randomized conditional p-values for testing HWE cannot be recommended for estimating the proportion of false hypotheses, their realized randomized counterparts should be used. P-values corresponding to the asymptotic unconditional chi-square test lead to reasonable estimates only if SNPs with low minor allele frequency are excluded. We provide an algorithm to compute the probability that SNPs violate HWE given the observed CR, which yields an improved measure of data quality. The proposed methods are applied to SNP data from the KORA (Cooperative Health Research in the Region of Augsburg, Southern Germany) 500 K project, a GWA study in a population-based sample genotyped by Affymetrix GeneChip 500 K arrays using the calling algorithm BRLMM 1.4.0. We show that all SNPs with CR = 100 per cent are nearly in perfect HWE wh...Continue Reading

References

Jan 16, 2002·American Journal of Human Genetics·Eric SobelKenneth Lange
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Jul 4, 2008·Hormone and Metabolic Research = Hormon- Und Stoffwechselforschung = Hormones Et Métabolisme·C HerderT Illig
Jul 11, 2008·BMC Bioinformatics·Korbinian Strimmer
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Citations

Aug 13, 2014·BMC Genetics·Nab Raj RoshyaraMarkus Scholz
Jan 21, 2020·Biometrical Journal. Biometrische Zeitschrift·Xiongzhi Chen
Jul 29, 2015·Statistical Applications in Genetics and Molecular Biology·Thorsten Dickhaus

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