Heid, I.M. ; Lamina, C. ; Küchenhoff, H.* ; Fischer, G. ; Klopp, N. ; Kolz, M. ; Grallert, H. ; Vollmert, C. ; Wagner, S. ; Huth, C. ; Müller, J.* ; Müller, M. ; Hunt, S.C.* ; Peters, A. ; Paulweber, B.* ; Wichmann, H.-E. ; Kronenberg, F.* ; Illig, T.
     
 
    
        
Estimating the Single Nucleotide Polymorphism Genotype Misclassification From Routine Double Measurements in a Large Epidemiologic Sample.
    
    
        
    
    
        
        Am. J. Epidemiol. 168, 878-889 (2008)
    
    
		
		
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			Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
		
     
    
		
		
			
				Previously, estimation of genotype misclassification of single nucleotide polymorphisms (SNPs) as encountered in epidemiologic practice and involving thousands of subjects was lacking. The authors collected representative data on approximately 14,000 subjects from 8 studies and 646,558 genotypes assessed in 2005 by means of matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Overall discordance among 57,805 double genotypes from routine quality control was 0.36%. Fitting different misclassification models by maximum likelihood assuming identical misclassification for all SNPs, the estimated misclassification probabilities ranged from 0.0000 to 0.0035. When applying the misclassification simulation and extrapolation (MC-SIMEX) method for the first time to genetic data to account for the misclassification in a reanalysis of adiponectin-encoding (APM1) gene SNP associations with plasma adiponectin in 1,770 subjects, the authors found no impact of this small error on association estimates but increased estimates for a more substantial error. This study is the first to provide large-scale epidemiologic data on SNP genotype misclassification. The estimated misclassification in this example was small and negligible for association estimates, which is reassuring and essential for detecting SNP associations. In situations with more substantial error, the presented approach using duplicate genotyping and the MC-SIMEX method is practical and helpful for quantifying the genotyping error and its impact.
			
			
				
			
		 
		
			
				
					
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        Publikationstyp
        Artikel: Journalartikel
    
 
    
        Dokumenttyp
        Wissenschaftlicher Artikel
    
 
    
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        Schlagwörter
        bias (epidemiology); genetics; genotype; likelihood functions; polymorphism; single nucleotide
    
 
    
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        Veröffentlichungsjahr
        2008
    
 
    
        Prepublished im Jahr 
        
    
 
    
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        2008
    
 
    
    
        ISSN (print) / ISBN
        0002-9262
    
 
    
        e-ISSN
        1476-6256
    
 
    
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	    Band: 168,  
	    Heft: 8,  
	    Seiten: 878-889 
	    Artikelnummer: ,  
	    Supplement: ,  
	
    
 
  
        
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            Verlag
            Oxford University Press
        
 
        
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        Begutachtungsstatus
        Peer reviewed
    
 
    
        Institut(e)
        Institute of Epidemiology (EPI)
    
 
    
        POF Topic(s)
        30503 - Chronic Diseases of the Lung and Allergies
    
 
    
        Forschungsfeld(er)
        Genetics and Epidemiology
    
 
    
        PSP-Element(e)
        G-503900-001
    
 
    
        Förderungen
        
    
 
    
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        Erfassungsdatum
        2008-12-19