Non-random error in genotype calling procedures: implications for family-based and case-control genome-wide association studies

Anney, Richard ORCID: https://orcid.org/0000-0002-6083-407X, Kenny, Elaine, O'Dushlaine, Colm T., Lasky-Su, Jessica, Franke, Barbara, Morris, Derek W., Neale, Benjamin M., Asherson, Philip, Faraone, Stephen V. and Gill, Michael 2008. Non-random error in genotype calling procedures: implications for family-based and case-control genome-wide association studies. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 147B (8) , pp. 1379-1386. 10.1002/ajmg.b.30836

Full text not available from this repository.

Abstract

The considerable data-handling requirements for genome wide association studies (GWAS) prohibit individual calling of genotypes and create a reliance on sophisticated “genotype-calling algorithms.” Despite their obvious utility, the current genotyping platforms and calling-algorithms used are not without their limitations. Specifically, some genotypes are not called due to the ambiguity of the data. Any bias in the missing data could create spurious results. Using data from the Genetic Analysis Information Network (GAIN) we observed that missing genotypes are not randomly distributed throughout the homozygous and heterozygous groups. Using simulation, we examined whether the level and type of missingness observed might influence deviation from the null-hypothesis under common case–control and family-based statistical approaches. Under a case–control model, where missingness is present in a case group but not the controls, we observed bias giving rise to genome-wide significant type-I error for missingness as low as 3%. The family-based association simulations show close to nominal type-I error at 4% genotype missingness. These findings have important implications to study design, quality-control procedures and reporting of findings in GWAS.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG) Medicine
Subjects:	R Medicine > R Medicine (General)
Uncontrolled Keywords:	GAIN;genome wide association study;genotyping bias;cluster plots
Publisher:	Wiley-Blackwell
ISSN:	1552-485X
Last Modified:	31 Oct 2022 10:32
URI:	https://orca.cardiff.ac.uk/id/eprint/85264

Citation Data

Cited 9 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item