用于相关个体和缺失数据的病例对照关联测试的BLUP基因型填充
BLUP genotype imputation for case-control association testing with related individuals and missing data.
作者信息
McPeek Mary Sara
机构信息
Departments of Statistics and Human Genetics, University of Chicago, Chicago, IL, USA.
出版信息
J Comput Biol. 2012 Jun;19(6):756-65. doi: 10.1089/cmb.2012.0024.
Abstract
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.
摘要
我们考虑在包含亲属个体的样本中进行病例对照关联测试的问题，在此我们假设家系结构是已知的。通常，对于每个测试的标记，一些个体将有缺失的基因型数据。针对这种情况，已提出MQLS方法用于关联测试。我们表明，MQLS方法等同于一种使用基于亲属基因型数据的最佳线性无偏预测器（BLUP）来估算缺失基因型的方法。从这个角度来看，MQLS能准确校正估算误差以及由于估算产生的额外相关性。我们还研究了这种BLUP估算方法在检测关联方面所提供的额外功效的大小。
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