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Non‐random error in genotype calling procedures: Implications for family‐based and case–control genome‐wide association studies
Author(s) -
Anney Richard J.L.,
Kenny Elaine,
O'Dushlaine Colm T.,
LaskySu Jessica,
Franke Barbara,
Morris Derek W.,
Neale Benjamin M.,
Asherson Philip,
Faraone Stephen V.,
Gill Michael
Publication year - 2008
Publication title -
american journal of medical genetics part b: neuropsychiatric genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.393
H-Index - 126
eISSN - 1552-485X
pISSN - 1552-4841
DOI - 10.1002/ajmg.b.30836
Subject(s) - missing data , spurious relationship , type i and type ii errors , genome wide association study , ambiguity , genotyping , genotype , genetic association , statistics , computer science , data mining , genetics , biology , mathematics , gene , single nucleotide polymorphism , programming language
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. © 2008 Wiley‐Liss, Inc.