BLUP genotype imputation for case-control association testing with related individuals and missing data.
We consider the problem of case-control association testing in samples that contain related individuals, where we assume the pedigree structure is known. Typically, for each marker tested, some individuals will have missing genotype data. The MQLS method has been proposed for association testing in this situation. We show that the MQLS method is equivalent to an approach in which missing genotypes are imputed using the best linear unbiased predictor (BLUP) based on relatives' genotype data. Viewed this way, the MQLS exactly corrects for the imputation error and for the extra correlation due to imputation. We also investigate the amount of additional power for detecting association that is provided by this BLUP imputation approach.
Departments of Statistics and Human Genetics, University of Chicago, Chicago, IL, USA. mcpeek@galton.uchicago.edu
Mary Sara
MS
McPeek
D000465:Algorithms; D016022:Case-Control Studies; D003198:Computer Simulation; D055106:Genome-Wide Association Study; D005838:Genotype; D006801:Humans; D008957:Models, Genetic; D010375:Pedigree; D020641:Polymorphism, Single Nucleotide