BLUP Genotype Imputation for Case-Control Association Testing with Related Individuals and Missing Data
نویسنده
چکیده
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.
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ورودعنوان ژورنال:
- Journal of computational biology : a journal of computational molecular cell biology
دوره 19 6 شماره
صفحات -
تاریخ انتشار 2012