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Parametric model‐based statistics for possible genotyping errors and sample stratification in sibling‐pair SNP data
Author(s) -
Korostishevsky Michael,
Malkin Ida,
Spector Tim,
Livshits Gregory
Publication year - 2010
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.20431
Subject(s) - statistics , snp , genotyping , parametric statistics , population stratification , parametric model , sibling , biology , mathematics , genetics , single nucleotide polymorphism , genotype , psychology , gene , developmental psychology
The detection of genotyping errors, based on apparent Mendelian incompatibilities in a sample of sib‐pairs, is a complicated problem. In the case of a single marker and unknown parental genotypes, all combinations of sib‐pair genotypes are self‐consistent. Moreover, the observed deviation from equilibrium genotype frequencies may result from genotyping errors as well as from the sample's stratification. This in turn, may profoundly affect the results of association and linkage analyses, and therefore an estimation of these factors should be done beforehand. Here we present several parametric models, and using likelihood ratio statistics, we suggest a method of combined analysis of genotyping errors and a sample stratification for randomly ascertained sib‐pair single nucleotide polymorphism (SNP) data. Specifically, we implemented two models of genotyping errors in either heterozygotes or homozygotes, and two models of sample stratification resulting from either the presence of families of different ethnic origin (e.g., a population admixture) or from a different ethnic origin of the parents in the family (e.g., intermarriage). The power of this method was established by Monte Carlo data simulation. The results clearly suggest that the proposed method is most efficient for detecting genotyping errors in heterozygotes, a common error caused by incorrect SNP data interpretation. We also provide an example of its application to real data. Genet. Epidemiol. 34:26–33, 2010. © 2009 Wiley‐Liss, Inc.